6 Why There?

6.1 Wordnets

6.1.1 US Undergraduate

6.1.1.1 Allen

6.1.1.1.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 10). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 63. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.1.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.2 Autzen Stadium

6.1.1.2.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 26). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 117 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.2.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 8). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 63 (n_Invalid = 4 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.3 Cemetery

6.1.1.3.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 20 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.3.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 1). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 28. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.4 Chapman

6.1.1.4.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 17). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 33. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.4.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5 Erb Memorial Union

6.1.1.5.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 34). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 977 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 269 students provided responses regarding one place, n = 222 provided responses regarding two places, and n = 88 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.2 Overall Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 97 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 38 students provided responses regarding one place, n = 16 provided responses regarding two places, and n = 9 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.5.3 Atrium East

6.1.1.5.3.1 Belong

6.1.1.5.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.4 Courtyard

6.1.1.5.4.1 Belong

6.1.1.5.4.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.5 Craft

6.1.1.5.5.1 Belong

6.1.1.5.5.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.6 Duck Nest

6.1.1.5.6.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 36. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.7 Falling Sky

6.1.1.5.7.1 Belong

6.1.1.5.7.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.8 Fishbowl

6.1.1.5.8.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 165. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.8.2 Don’t Belong

6.1.1.5.9 Fresh Market

6.1.1.5.9.1 Belong

6.1.1.5.9.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.10 LGBTQA3

6.1.1.5.10.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 5). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 56. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.10.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.11 Mills Center

6.1.1.5.11.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 59 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.11.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.12 Multicultural Center

6.1.1.5.12.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 5). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 112. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.12.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.13 O Lounge

6.1.1.5.13.1 Belong

6.1.1.5.13.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.14 Taylor Lounge

6.1.1.5.14.1 Belong

6.1.1.5.14.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.5.15 Women’s Center

6.1.1.5.15.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 32). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 125. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first- and second-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.5.15.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.6 Frohnmayer

6.1.1.6.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 15). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 52. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.6.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 21 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.7 Hayward Field

6.1.1.7.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.7.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 148 (n_Invalid = 3 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.8 HEDCO

6.1.1.8.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 31. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.8.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.9 Jaqua

6.1.1.9.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.9.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 31). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 74 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.10 Knight Law

6.1.1.10.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.10.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 25). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 57. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.11 Lawrence

6.1.1.11.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 5). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 86. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.11.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.12 Library

6.1.1.12.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 21). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 663 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.12.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 207. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.13 Lillis Business Complex

6.1.1.13.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 30). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 197 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.13.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 42). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 263 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.14 Lokey Science Complex

6.1.1.14.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 31). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 299 (n_Invalid = 5 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 207 students provided responses regarding one place, n = 35 provided responses regarding two places, n = 6 provided responses regarding three places, and n = 1 provided responses regarding four places within the Lokey Complex. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.2 Overall Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 14). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 175 (n_Invalid = 7 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 129 students provided responses regarding one place, n = 18 provided responses regarding two places, n = 2 provided responses regarding three places, and n = 1 provided responses regarding four places within the Lokey Complex. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.14.3 Columbia

6.1.1.14.3.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 42. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.14.4 Klamath

6.1.1.14.4.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 5). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 34 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.4.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 33 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.14.5 Lewis

6.1.1.14.5.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 23 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.5.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 28. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.14.6 Science Commons

6.1.1.14.6.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 9). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 88. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.14.7 Willamette

6.1.1.14.7.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 7). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 64. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.14.7.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 52 (n_Invalid = removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.15 Matthew Knight Arena

6.1.1.15.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 12). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 47. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.15.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 66 (n_Invalid = 4 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.16 McKenzie

6.1.1.16.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 29 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.16.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.17 Oregon

6.1.1.17.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 33. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.17.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.18 Straub

6.1.1.18.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 18). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 56. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.18.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.19 Student Rec Complex

6.1.1.19.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 15). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 692 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.19.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 10). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 575 (n_Invalid = 11 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.20 Tykeson

6.1.1.20.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 73 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.20.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.21 University Health Services

6.1.1.21.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 27. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.21.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.22 University Housing

6.1.1.22.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 32). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 933 (n_Invalid = 7 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 619 students provided responses regarding one place, n = 136 provided responses regarding two places, and n = 14 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.2 Overall Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 3, max = 22). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 2. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 487 (n_Invalid = 10 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 619 students provided responses regarding one place, n = 136 provided responses regarding two places, and n = 14 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.3 Barnhart

6.1.1.22.3.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 27 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.22.4 Bean

6.1.1.22.4.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 7). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 136 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.4.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 57. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.5 Carson

6.1.1.22.5.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 85 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.5.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 34 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.6 Earl

6.1.1.22.6.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 51 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.1.22.7 Global Scholars

6.1.1.22.7.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 151. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.7.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 93 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.8 Hamilton

6.1.1.22.8.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 9). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 175 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.8.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 7). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 64. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.9 Kalapuya Ilihi

6.1.1.22.9.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 90. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.9.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 2, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 58 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.10 Living Learning

6.1.1.22.10.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 5). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 75 (n_Invalid = 0 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.10.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 49. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.11 Unthank

6.1.1.22.11.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 3). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 70. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.11.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 6). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 52 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.1.22.12 Walton

6.1.1.22.12.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 4). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 54. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.1.22.12.2 Don’t Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 32. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the mako palette of the viridis package.

6.1.2 International

6.1.2.1 Erb Memorial Union

6.1.2.1.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 10). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 72 (n_Invalid = 2 removed). Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 24 students provided responses regarding one place, n = 15 provided responses regarding two places, and n = 6 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.1.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.2.1.3 Mills Center

6.1.2.1.3.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 10). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 26. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.1.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.2.2 Library

6.1.2.2.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 1). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 51. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.2.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.2.3 Lokey Science Complex

6.1.2.3.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22 (n_Invalid = 1 removed). Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 14 students provided responses regarding one place and n = 4 provided responses regarding two places. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.3.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.2.4 Student Rec Complex

6.1.2.4.1 Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 1). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 37. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.4.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.2.5 University Housing

6.1.2.5.1 Overall Belong

Note: Wordnet = adjacent (\(\le\) 1 word apart) adjective-noun bigrams visualized as a network. Line thickness represents frequency of cooccurrence (min = 1, max = 2). The criterion for inclusion of bigram in the wordnet was cooccurrence \(\gt\) 0. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 40. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 27 students provided responses regarding one place, n = 2 provided responses regarding two places, and n = 3 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordnet was generated using the ggraph and igraph packages. Colors were produced using the rocket palette of the viridis package.

6.1.2.5.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.3 Graduate

6.1.3.1 Library

6.1.3.1.1 Belong

6.1.3.1.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.1.3.2 Student Rec Complex

6.1.3.2.1 Belong

6.1.3.2.2 Don’t Belong

6.2 Wordclouds

6.2.1 US Undergraduate

6.2.1.1 Allen

6.2.1.1.1 Belong

## $x
## $x$word
##  [1] "advertising major"  "journalism major"   "journalism student"
##  [4] "hall"               "journalism"         "major"             
##  [7] "student"            "work"               "year"              
## [10] "friend"             "kind"               "space"             
## [13] "staff"              "building"           "class"             
## [16] "faculty"            "helpful"            "people"            
## [19] "sojc"               "teacher"            "time"              
## [22] "professor"          "campus"             "comfortable"       
## [25] "day"                "friendhip"          "home"              
## [28] "nice"               "school"            
## 
## $x$freq
##  [1]  2  9  4  2  2 13  7  2  2  9  2  2  2  9 10  3  3 10  7  4 10  6  3  4  2
## [26]  2  2  2  5
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 13.84615
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 63. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.1.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.2 Autzen Stadium

6.2.1.2.1 Belong

## $x
## $x$word
##  [1] "other student"   "big family"      "good memory"     "football fan"   
##  [5] "same thing"      "favorite memory" "sporting event"  "football season"
##  [9] "school spirit"   "best memory"     "only thing"      "good time"      
## [13] "student body"    "student section" "freshman year"   "football game"  
## [17] "marching band"   "high school"     "whole school"    "duck fan"       
## [21] "game day"        "football team"   "favorite sport"  "great time"     
## [25] "favorite place"  "best place"      "family"          "football"       
## [29] "thing"           "people"          "great"           "experience"     
## [33] "student"         "energy"          "game"            "member"         
## [37] "pride"           "time"            "band"            "school"         
## [41] "team"            "college"         "home"            "oregon"         
## [45] "sport"           "year"            "fun"             "stadium"        
## [49] "duck"            "community"       "campus"          "full"           
## [53] "welcoming"       "uo"              "atmosphere"      "comfortable"    
## [57] "connection"      "love"            "reason"          "welcome"        
## [61] "friend"          "part"            "happy"           "sense"          
## [65] "able"            "bigger"          "cheer"           "classmate"      
## [69] "connect"         "eugene"          "excited"         "excitement"     
## [73] "fall"            "field"           "gameday"         "kid"            
## [77] "major"           "matter"          "nice"            "omb"            
## [81] "one"             "proud"           "rehearsal"       "special"        
## [85] "stand"           "support"         "type"            "university"     
## [89] "world"          
## 
## $x$freq
##  [1]  3  2  2  2  3  2  2  3  2  2  2  2  2  9  3 23  8  2  2  5  5  5  2  2  2
## [26]  2  2 12  3  4  3  2 11  4 22  2  2  3 11  6  6  3  2  4  5  4  8  7 23  8
## [51]  2  2  2  5  6  3  3  3  3  3 15  4  6  6  4  2  3  2  6  2  5  2  3  2  2
## [76]  2  3  3  2  2  2  3  5  2  3  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 7.826087
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.2.2 Don’t Belong

## $x
## $x$word
##  [1] "greek life"      "student section" "sport person"    "football game"  
##  [5] "large crowd"     "uo"              "student"         "football"       
##  [9] "people"          "sport"           "crowd"           "game"           
## [13] "team"            "big"             "stadium"         "thing"          
## [17] "friend"          "atmosphere"      "comfortable"     "experience"     
## [21] "field"           "part"            "rowdy"           "scene"          
## [25] "time"            "university"     
## 
## $x$freq
##  [1]  2  2  3  8  2  2  5  6  8 15  3 12  2  3  3  6  8  4  2  2  2  3  2  3  4
## [26]  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 12
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = (n_Invalid = 4 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.3 Cemetery

6.2.1.3.1 Belong

## $x
## $x$word
##  [1] "many people" "good place"  "people"      "nice"        "campus"     
##  [6] "tree"        "class"       "day"         "flower"      "minute"     
## [11] "morning"     "nature"      "peaceful"    "quiet"       "seriousness"
## 
## $x$freq
##  [1] 2 2 2 4 8 4 2 3 2 2 2 2 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 20 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.3.2 Don’t Belong

## $x
## $x$word
## [1] "creepy" "way"    "dead"   "scary"  "spooky"
## 
## $x$freq
## [1] 3 2 4 4 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 45
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 28. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.4 Chapman

6.2.1.4.1 Belong

## $x
## $x$word
##  [1] "honor college" "chapman hall"  "chc student"   "student"      
##  [5] "home"          "space"         "building"      "class"        
##  [9] "part"          "quiet"         "best"          "friendly"     
## [13] "people"        "faculty"       "comfortable"   "helpful"      
## [17] "sense"         "time"          "welcome"      
## 
## $x$freq
##  [1] 13  3  2  5  2  2  2  6  2  3  2  2  6  4  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 13.84615
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 33. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.4.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5 Erb Memorial Union

6.2.1.5.1 Overall Belong

## $x
## $x$word
##   [1] "mental health"           "good spot"              
##   [3] "international student"   "good vibe"              
##   [5] "calming environment"     "good environment"       
##   [7] "good memory"             "familiar face"          
##   [9] "first year"              "same thing"             
##  [11] "traditional student"     "student group"          
##  [13] "different craft"         "duck nest"              
##  [15] "duck store"              "cultural club"          
##  [17] "mills center"            "womens center"          
##  [19] "south atrium"            "east atrium"            
##  [21] "self care"               "good job"               
##  [23] "multicultural center"    "free printing"          
##  [25] "craft center"            "good place"             
##  [27] "fellow student"          "common place"           
##  [29] "different culture"       "similar background"     
##  [31] "background noise"        "relaxed vibe"           
##  [33] "nice spot"               "open environment"       
##  [35] "favorite place"          "different activity"     
##  [37] "other student"           "diverse group"          
##  [39] "own business"            "bad experience"         
##  [41] "good resource"           "relaxed environment"    
##  [43] "food option"             "fish bowl"              
##  [45] "language circle"         "lgbtq community"        
##  [47] "many resource"           "of lounge"              
##  [49] "own thing"               "campus life"            
##  [51] "only place"              "welcoming environment"  
##  [53] "great place"             "queer student"          
##  [55] "front desk"              "nice environment"       
##  [57] "few time"                "lgbtqa3 center"         
##  [59] "gender identity"         "good time"              
##  [61] "woman center"            "great resource"         
##  [63] "lgbtqia community"       "best place"             
##  [65] "relaxing place"          "many event"             
##  [67] "many time"               "positive experience"    
##  [69] "esport lounge"           "certain way"            
##  [71] "great way"               "food vendor"            
##  [73] "work do"                 "therapy dog"            
##  [75] "freshman year"           "chill place"            
##  [77] "many people"             "female student"         
##  [79] "school work"             "safe place"             
##  [81] "much time"               "wide variety"           
##  [83] "comfortable environment" "most people"            
##  [85] "new people"              "open space"             
##  [87] "great time"              "queer person"           
##  [89] "safe space"              "courtyard dining"       
##  [91] "cool place"              "welcoming place"        
##  [93] "fewer people"            "nice mix"               
##  [95] "great people"            "amazing place"          
##  [97] "welcoming space"         "nice place"             
##  [99] "busy area"               "other people"           
## [101] "fall sky"                "option"                 
## [103] "relaxed atmosphere"      "spot"                   
## [105] "nice space"              "quiet place"            
## [107] "new friend"              "nice table"             
## [109] "group"                   "welcoming atmosphere"   
## [111] "good"                    "social"                 
## [113] "college"                 "nice atmosphere"        
## [115] "comfortable place"       "fun place"              
## [117] "student worker"          "environment"            
## [119] "comfortable space"       "study"                  
## [121] "center"                  "chair"                  
## [123] "comfy"                   "creative"               
## [125] "memory"                  "office"                 
## [127] "similar"                 "store"                  
## [129] "fun space"               "great"                  
## [131] "school"                  "familiar"               
## [133] "own"                     "craft"                  
## [135] "project"                 "student"                
## [137] "background"              "desk"                   
## [139] "help"                    "supplies"               
## [141] "feeling"                 "organization"           
## [143] "such"                    "tea"                    
## [145] "thing"                   "experience"             
## [147] "open"                    "chill"                  
## [149] "positive"                "queer"                  
## [151] "club"                    "asian"                  
## [153] "available"               "comforting"             
## [155] "feel"                    "hangout"                
## [157] "light"                   "tran"                   
## [159] "safe"                    "area"                   
## [161] "relaxed"                 "culture"                
## [163] "mill"                    "room"                   
## [165] "support"                 "meeting"                
## [167] "year"                    "activity"               
## [169] "bathroom"                "circle"                 
## [171] "cool"                    "dedicated"              
## [173] "game"                    "location"               
## [175] "market"                  "private"                
## [177] "relax"                   "welcoming"              
## [179] "uo"                      "space"                  
## [181] "person"                  "resource"               
## [183] "amazing"                 "diverse"                
## [185] "female"                  "lgbtqa3"                
## [187] "productive"              "table"                  
## [189] "nice"                    "woman"                  
## [191] "community"               "ceramics"               
## [193] "conversation"            "busy"                   
## [195] "lounge"                  "way"                    
## [197] "quiet"                   "atmosphere"             
## [199] "food"                    "coworker"               
## [201] "diversity"               "dog"                    
## [203] "energy"                  "enough"                 
## [205] "gay"                     "inviting"               
## [207] "meal"                    "minority"               
## [209] "music"                   "sky"                    
## [211] "stress"                  "warm"                   
## [213] "willing"                 "work"                   
## [215] "day"                     "employee"               
## [217] "identity"                "event"                  
## [219] "time"                    "cozy"                   
## [221] "supportive"              "variety"                
## [223] "calm"                    "happy"                  
## [225] "seat"                    "veteran"                
## [227] "comfortable"             "starbuck"               
## [229] "courtyard"               "fun"                    
## [231] "people"                  "computer"               
## [233] "customer"                "dorm"                   
## [235] "full"                    "issue"                  
## [237] "judgement"               "service"                
## [239] "slice"                   "term"                   
## [241] "week"                    "window"                 
## [243] "pizza"                   "friendly"               
## [245] "coffee"                  "staff"                  
## [247] "comfort"                 "art"                    
## [249] "kind"                    "anxious"                
## [251] "inclusive"               "part"                   
## [253] "seating"                 "sport"                  
## [255] "connection"              "member"                 
## [257] "access"                  "close"                  
## [259] "opportunity"             "piano"                  
## [261] "poc"                     "snack"                  
## [263] "worker"                  "easy"                   
## [265] "break"                   "class"                  
## [267] "welcome"                 "friend"                 
## [269] "campus"                  "lunch"                  
## [271] "helpful"                 "homework"               
## [273] "one"                     "able"                   
## [275] "academics"               "accessible"             
## [277] "addition"                "age"                    
## [279] "ambiance"                "apart"                  
## [281] "assistance"              "attention"              
## [283] "backgrounds"             "beer"                   
## [285] "better"                  "bisexual"               
## [287] "bite"                    "board"                  
## [289] "boot"                    "boss"                   
## [291] "bright"                  "bunch"                  
## [293] "bustle"                  "clean"                  
## [295] "clear"                   "color"                  
## [297] "connect"                 "convenient"             
## [299] "couch"                   "crowded"                
## [301] "desperate"               "dinner"                 
## [303] "discrimination"          "display"                
## [305] "ease"                    "else"                   
## [307] "enthusiastic"            "family"                 
## [309] "fishbowl"                "general"                
## [311] "genuine"                 "hard"                   
## [313] "heart"                   "home"                   
## [315] "hustle"                  "interested"             
## [317] "involved"                "judgemental"            
## [319] "judgment"                "layout"                 
## [321] "like"                    "matter"                 
## [323] "mcc"                     "mic"                    
## [325] "mind"                    "nap"                    
## [327] "nsu"                     "outlet"                 
## [329] "pads"                    "papers"                 
## [331] "party"                   "peace"                  
## [333] "peaceful"                "peer"                   
## [335] "pressure"                "question"               
## [337] "respectful"              "rest"                   
## [339] "roommate"                "routine"                
## [341] "sad"                     "sense"                  
## [343] "studying"                "sure"                   
## [345] "team"                    "tv"                     
## [347] "type"                    "uncomfortable"          
## [349] "use"                     "wc"                     
## [351] "workshop"                "worried"                
## [353] "worry"                  
## 
## $x$freq
##   [1]   3   3   2   3   2   5   2   5   2   2   3   2   2  21   2   2   2   5
##  [19]   3   2   2   2  12   5  12  19   2   3   2   2   2   2   2   3  10   2
##  [37]  10   2   7   2   2   2   2   3   4   5   6   5   7   2   4   6  26   3
##  [55]   3   7  11   3   2   3  32   3   2   5   4   2   2   4   2   2   3   2
##  [73]   2   2   4   2   9   2   8   9   2   2   2   5   3   8   2   2  13   2
##  [91]   2   6   2   2   2   2   3  33   2   6   2   2   2   4   6   3   2   2
## [109]   2   3   5   4   4   2   5   4   2  10   3  15   9   2   2   2   2   3
## [127]   3   2   2  10   8   4   3   3   4  34   5   2   4   2   2   3   2   3
## [145]  11   8  11   4   2   7   6   2   2   2   2   3   2   3  15  18   3   3
## [163]   6   5   6   6   8   6   2   2   5   2   3   3   2   2   2  27   7  54
## [181]  11  17   5   2   2   2   2   4  80  42  19   3   3   5  10   7  14  20
## [199]  33   2   3   2   2   2   5   2   2   2   5   4   3   2   4  26   6   5
## [217]   5  14  50   5   5   4   3   3   3   3  35  11   5  20 177   2   2   2
## [235]   2   2   5   4   2   4   2   6  12  38   7  33   5   8  18   3   6  12
## [253]   3   3   7   7   4   4   4  16   4   4  14  10   6  36  30 140  43  20
## [271]  22  48  18  29   2   2   3   2   2   3   2   2   2   4   2   2   3   2
## [289]   4   2   2   2   2   2   3  17   5   2   2   3   2   2   2   2   3   5
## [307]   2   2  28   2   3   2   2   7   2   2   2   2   2   2   2   3   6   2
## [325]   2   4   4   3   2   3   3   4   5  10   2   5   4   2   2   2   2   6
## [343]   2   3   2   2   3   2   2   2   2   2   2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 1.016949
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 977 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 24 students provided responses regarding one place, n = 15 provided responses regarding two places, and n = 6 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.5.2 Overall Don’t Belong

## $x
## $x$word
##  [1] "hawaii club"          "high school"          "social student"      
##  [4] "big fan"              "social anxiety"       "big group"           
##  [7] "wide group"           "multicultural center" "many people"         
## [10] "student"              "social place"         "social"              
## [13] "loud people"          "craft"                "group"               
## [16] "area"                 "center"               "culture"             
## [19] "space"                "busy"                 "same"                
## [22] "crowd"                "table"                "person"              
## [25] "people"               "part"                 "time"                
## [28] "friend"               "alone"                "anxious"             
## [31] "campus"               "comfortable"          "creativity"          
## [34] "crowded"              "day"                  "different"           
## [37] "difficult"            "esport"               "fault"               
## [40] "feel"                 "fishbowl"             "folk"                
## [43] "hard"                 "immature"             "introverted"         
## [46] "money"                "older"                "outsider"            
## [49] "printer"              "type"                 "uncomfortable"       
## [52] "unwelcoming"          "welcome"             
## 
## $x$freq
##  [1]  2  2  2  2  4  2  2  3  6  2  2  2  2  2  4  5  3  3  6  3  3  2  2  3 30
## [26]  8  7 19  2  4  6  4  2  2  2  2  2  2  2  3  3  3  3  2  2  2  2  2  2  2
## [51]  3  3  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 6
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 97 (n_Invalid = 1 removed) Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 24 students provided responses regarding one place, n = 15 provided responses regarding two places, and n = 6 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.5.3 Atrium East

6.2.1.5.3.1 Belong

## $x
## $x$word
## [1] "great place"   "nice place"    "other student" "work"         
## [5] "class"         "friend"        "homework"      "lunch"        
## 
## $x$freq
## [1] 3 7 3 4 2 8 3 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.4 Courtyard

6.2.1.5.4.1 Belong

## $x
## $x$word
##  [1] "nice place"       "good place"       "great place"      "food vendor"     
##  [5] "school"           "courtyard dining" "work"             "food"            
##  [9] "area"             "people"           "lunch"            "friend"          
## [13] "class"            "homework"         "comfortable"      "time"            
## [17] "able"             "attention"        "bite"             "break"           
## [21] "campus"           "emu"              "one"             
## 
## $x$freq
##  [1]  3  3  4  2  2  2  3  6  3  6  5 18  3  8  5  6  2  2  2  2  2  3  5
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 10
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.4.2 Don’t Belong

6.2.1.5.5 Craft

6.2.1.5.5.1 Belong

## $x
## $x$word
##  [1] "school work"           "different craft"       "welcoming environment"
##  [4] "few time"              "creative"              "craft"                
##  [7] "cool"                  "people"                "great"                
## [10] "ceramics"              "welcoming"             "thing"                
## [13] "time"                  "experience"            "resource"             
## [16] "student"               "area"                  "class"                
## [19] "year"                  "fun"                   "space"                
## [22] "art"                   "welcome"               "nice"                 
## [25] "activity"              "amazing"               "campus"               
## [28] "easy"                  "friendly"              "helpful"              
## [31] "part"                  "staff"                 "variety"              
## [34] "workshop"             
## 
## $x$freq
##  [1]  2  2  2  3  2  3  2  6  2  3  3  4  4  3  3  3  2  6  4  5  5  8  4  8  2
## [26]  2  3  2  4  4  2 11  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 16.36364
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.5.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.6 Duck Nest

6.2.1.5.6.1 Belong

## $x
## $x$word
##  [1] "mental health"   "great place"     "welcoming place" "therapy dog"    
##  [5] "welcoming"       "nice"            "staff"           "space"          
##  [9] "dog"             "time"            "able"            "better"         
## [13] "campus"          "comfortable"     "ease"            "environment"    
## [17] "event"           "feel"            "kind"            "people"         
## [21] "such"            "supportive"      "tea"            
## 
## $x$freq
##  [1] 3 3 3 2 3 2 2 4 2 2 2 2 3 2 2 2 3 2 5 6 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 30
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.7 Falling Sky

6.2.1.5.7.1 Belong

## $x
## $x$word
##  [1] "good memory" "good place"  "nice place"  "food"        "nice"       
##  [6] "atmosphere"  "pizza"       "slice"       "space"       "people"     
## [11] "beer"        "campus"      "chill"       "class"       "easy"       
## [16] "friend"      "friendly"    "homework"    "study"       "worker"     
## 
## $x$freq
##  [1]  2  2  2  4  4  4 11  2  3  4  4  4  3  3  2  9  6  2  2  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 16.36364
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.7.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.8 Fishbowl

6.2.1.5.8.1 Belong

## $x
## $x$word
##  [1] "nice environment"  "own thing"         "good place"       
##  [4] "fish bowl"         "great place"       "open space"       
##  [7] "own business"      "many people"       "common place"     
## [10] "fellow student"    "nice place"        "most people"      
## [13] "spot"              "space"             "study"            
## [16] "comfortable place" "fun place"         "school work"      
## [19] "nice"              "open"              "event"            
## [22] "area"              "community"         "light"            
## [25] "student"           "food"              "welcoming"        
## [28] "window"            "work"              "starbuck"         
## [31] "school"            "people"            "comfortable"      
## [34] "fun"               "atmosphere"        "easy"             
## [37] "seat"              "time"              "friendly"         
## [40] "one"               "campus"            "coffee"           
## [43] "friend"            "able"              "accessible"       
## [46] "boot"              "bustle"            "class"            
## [49] "else"              "emu"               "homework"         
## [52] "hustle"            "judgement"         "lunch"            
## [55] "peer"              "project"           "seating"          
## [58] "uncomfortable"     "welcome"          
## 
## $x$freq
##  [1]  3  3  4  2  3  5  2  2  2  2  4  2  2  3  5  2  2  3 11  4  2  6  2  2  6
## [26] 15  2  2  4  9  4 34  5  5  4  2  2 12  3  4 10  5 45  8  2  2  2  9  2  3
## [51] 12  2  2  7  2  2  3  2  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 4
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.8.2 Don’t Belong

## $x
## $x$word
##  [1] "many people" "student"     "people"      "space"       "friend"     
##  [6] "area"        "busy"        "campus"      "day"         "immature"   
## [11] "time"       
## 
## $x$freq
##  [1]  2  2  8  4 10  3  3  3  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 18
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.9 Fresh Market

6.2.1.5.9.1 Belong

## $x
## $x$word
##  [1] "favorite place" "class"          "snack"          "friendly"      
##  [5] "worker"         "nice"           "day"            "employee"      
##  [9] "emu"            "food"           "friend"         "lunch"         
## [13] "people"         "staff"          "welcome"       
## 
## $x$freq
##  [1] 2 2 2 6 4 6 2 2 3 5 3 2 5 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 30
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.9.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.10 LGBTQA3

6.2.1.5.10.1 Belong

## $x
## $x$word
##  [1] "many people"       "queer person"      "lgbtq community"  
##  [4] "few time"          "lgbtqia community" "people"           
##  [7] "queer student"     "only place"        "safe space"       
## [10] "queer"             "tran"              "community"        
## [13] "great"             "student"           "safe"             
## [16] "event"             "gay"               "identity"         
## [19] "meeting"           "kind"              "open"             
## [22] "resource"          "welcome"           "space"            
## [25] "friend"            "bisexual"          "board"            
## [28] "campus"            "helpful"           "member"           
## [31] "nice"              "part"             
## 
## $x$freq
##  [1] 2 2 5 2 2 3 3 2 2 7 3 5 2 4 6 3 5 2 2 2 2 4 2 9 3 2 2 6 2 4 7 5
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 20
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.10.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.11 Mills Center

6.2.1.5.11.1 Belong

## $x
## $x$word
##  [1] "language circle"   "good place"        "different culture"
##  [4] "great place"       "environment"       "many people"      
##  [7] "mill"              "student"           "space"            
## [10] "cozy"              "diversity"         "friendly"         
## [13] "nice"              "welcome"           "event"            
## [16] "staff"             "people"            "comfortable"      
## [19] "apart"             "backgrounds"       "campus"           
## [22] "friend"            "fun"               "homework"         
## [25] "mic"               "peaceful"          "time"             
## 
## $x$freq
##  [1]  4  3  2  2  2  2  5  3  4  3  2  4  8  4  3  4 23  6  2  2  2  5  2  2  2
## [26]  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 7.826087
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.11.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.12 Multicultural Center

6.2.1.5.12.1 Belong

## $x
## $x$word
##  [1] "cultural club"      "great place"        "few time"          
##  [4] "safe space"         "similar background" "student"           
##  [7] "nice space"         "activity"           "office"            
## [10] "nice place"         "similar"            "other people"      
## [13] "club"               "center"             "background"        
## [16] "culture"            "meeting"            "space"             
## [19] "organization"       "uo"                 "comfortable"       
## [22] "minority"           "welcoming"          "time"              
## [25] "staff"              "nice"               "person"            
## [28] "asian"              "environment"        "part"              
## [31] "welcome"            "community"          "friend"            
## [34] "people"             "poc"                "able"              
## [37] "campus"             "circle"             "color"             
## [40] "connection"         "emu"                "friendly"          
## [43] "helpful"            "home"               "homework"          
## [46] "open"               "peer"               "room"              
## 
## $x$freq
##  [1]  2  3  2  3  2  5  2  2  2  4  2  2  3  4  2  2  2  8  2  4  2  2  5  4  3
## [26] 10  6  2  2  2  2  3 15 33  4  7  4  2 12  3  2  5  4  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 5.454545
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.12.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.13 O Lounge

6.2.1.5.13.1 Belong

## $x
## $x$word
##  [1] "good environment" "good place"       "own thing"        "favorite place"  
##  [5] "great place"      "relaxing place"   "nice place"       "most people"     
##  [9] "good"             "study"            "comfortable"      "work"            
## [13] "nice"             "game"             "space"            "area"            
## [17] "student"          "emu"              "sport"            "time"            
## [21] "people"           "homework"         "friend"           "able"            
## [25] "class"            "close"            "community"        "display"         
## [29] "dorm"             "food"             "fun"              "one"             
## [33] "party"            "quiet"            "respectful"       "room"            
## [37] "sense"            "sky"              "tv"              
## 
## $x$freq
##  [1]  2  4  2  3  4  2  3  2  2  5  4  5  5  2  4  3  4  2  2  4 17 12 17  3  2
## [26]  2  2  2  2  2  2  4  3  5  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 10.58824
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.13.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.14 Taylor Lounge

6.2.1.5.14.1 Belong

## $x
## $x$word
##  [1] "favorite place" "best place"     "nice place"     "nice"          
##  [5] "quiet"          "space"          "music"          "comfortable"   
##  [9] "people"         "piano"          "atmosphere"     "class"         
## [13] "cozy"           "emu"            "homework"       "peaceful"      
## [17] "welcome"       
## 
## $x$freq
##  [1]  3  2  2  2  4  3  4  2 11 16  5  2  2  3  3  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 11.25
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.14.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.5.15 Women’s Center

6.2.1.5.15.1 Belong

## $x
## $x$word
##  [1] "many resource"  "free printing"  "good resource"  "female student"
##  [5] "woman center"   "few time"       "safe space"     "safe place"    
##  [9] "student"        "safe"           "year"           "resource"      
## [13] "welcoming"      "female"         "space"          "woman"         
## [17] "atmosphere"     "friendly"       "people"         "access"        
## [21] "emu"            "identity"       "time"           "comfortable"   
## [25] "service"        "work"           "kind"           "inclusive"     
## [29] "campus"         "nice"           "helpful"        "able"          
## [33] "assistance"     "clear"          "club"           "color"         
## [37] "comfort"        "community"      "connect"        "friend"        
## [41] "genuine"        "help"           "pads"           "papers"        
## [45] "peer"           "question"       "staff"          "support"       
## [49] "supportive"     "thing"          "way"            "wc"            
## [53] "welcome"        "willing"       
## 
## $x$freq
##  [1]  4  5  2  2 31  2  7  5  3  7  2  9  8  2 10 41  3  5 14  2  2  2  8  3  3
## [26]  3  7  4  5 11  9  2  2  2  2  3  2  2  2  2  2  2  2  3  3  2  6  3  2  2
## [51]  3  2  7  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 4.390244
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.5.15.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.6 Frohnmayer

6.2.1.6.1 Belong

## $x
## $x$word
##  [1] "band"           "music major"    "music majors"   "music building"
##  [5] "high school"    "student"        "music"          "building"      
##  [9] "friend"         "staff"          "school"         "people"        
## [13] "class"          "time"           "comfortable"    "dance"         
## [17] "dorm"           "friendly"       "home"           "one"           
## [21] "part"           "peer"           "performance"    "professor"     
## [25] "uo"            
## 
## $x$freq
##  [1]  2 14  2  4  2  2 14 10  9  2  7 13  8  9  2  2  2  2  5  2  2  4  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 12.85714
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 52. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.6.2 Don’t Belong

## $x
## $x$word
##  [1] "music major"    "good enough"    "music teacher"  "music student" 
##  [5] "music building" "student"        "music"          "class"         
##  [9] "building"       "people"        
## 
## $x$freq
##  [1]  3  2  2  3  2  2 11  2  6  5
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 16.36364
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 21 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.7 Hayward Field

6.2.1.7.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.7.2 Don’t Belong

## $x
## $x$word
##  [1] "greek life"    "sport culture" "sport people"  "sport person" 
##  [5] "year"          "people"        "athletic type" "other area"   
##  [9] "new"           "uo"            "building"      "field"        
## [13] "student"       "athletic"      "fan"           "thing"        
## [17] "sport"         "annoying"      "bit"           "crowd"        
## [21] "game"          "money"         "sporty"        "unwelcoming"  
## [25] "area"          "athlete"       "university"    "campus"       
## [29] "event"         "open"          "construction"  "able"         
## [33] "bad"           "close"         "comfortable"   "conscious"    
## [37] "contractor"    "fact"          "fat"           "gym"          
## [41] "hard"          "interested"    "jock"          "location"     
## [45] "rest"          "straights"    
## 
## $x$freq
##  [1]  2  2  2  3  3  2  2  2  2  2  3  7  7  6  2  2 32  2  2  2  2  4  2  2  7
## [26]  8  5  3  3  5 30  5  2  2  2  2  2  2  2  2  6  3  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 5.625
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 148 (n_Invalid = 3 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.8 HEDCO

6.2.1.8.1 Belong

## $x
## $x$word
##  [1] "fh program"      "education major" "fh major"        "welcoming place"
##  [5] "major class"     "major"           "nice"            "welcoming"      
##  [9] "people"          "comfortable"     "staff"           "building"       
## [13] "class"           "advisor"         "friendly"        "homework"       
## [17] "majority"        "student"         "time"           
## 
## $x$freq
##  [1] 2 2 2 2 2 3 5 2 6 4 3 7 7 2 2 2 2 2 6
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 25.71429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 31. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.8.2 Don’t Belong

## $x
## $x$word
## [1] "education major" "education class" "major"           "class"          
## [5] "building"        "department"     
## 
## $x$freq
## [1] 2 2 2 4 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 45
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.9 Jaqua

6.2.1.9.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.9.2 Don’t Belong

## $x
## $x$word
##  [1] "coffee shop"     "regular student" "student athlete" "space"          
##  [5] "student"         "center"          "athlete"         "university"     
##  [9] "school"          "people"          "campus"          "building"       
## [13] "access"          "cafe"            "class"           "exclusive"      
## [17] "fact"            "rest"            "sure"            "way"            
## [21] "welcome"        
## 
## $x$freq
##  [1]  2  2 31  2  9  2 26  2  3  2  6 26  2  2  4  5  2  2  2  3  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 5.806452
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 74 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.10 Knight Law

6.2.1.10.1 Belong

Note: There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.10.2 Don’t Belong

## $x
## $x$word
##  [1] "law student" "law"         "student"     "exclusive"   "library"    
##  [6] "building"    "inferior"    "life"        "people"      "quiet"      
## [11] "space"       "sure"        "undergrad"  
## 
## $x$freq
##  [1] 24  5  3  2  2 11  2  2  2  3  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 7.5
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 57. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.11 Lawrence

6.2.1.11.1 Belong

## $x
## $x$word
##  [1] "architecture student" "architecture major"   "design student"      
##  [4] "art student"          "favorite place"       "great place"         
##  [7] "best friend"          "design major"         "art minor"           
## [10] "similar interest"     "design library"       "many class"          
## [13] "many people"          "architecture"         "major"               
## [16] "design"               "environment"          "friend"              
## [19] "art"                  "interest"             "library"             
## [22] "experience"           "class"                "people"              
## [25] "space"                "studio"               "home"                
## [28] "nice"                 "creativity"           "familiar"            
## [31] "work"                 "time"                 "hearth"              
## [34] "community"            "building"             "comfortable"         
## [37] "able"                 "advisor"              "college"             
## [40] "connect"              "connection"           "day"                 
## [43] "feel"                 "friendly"             "helpful"             
## [46] "homework"             "lawerence"            "peer"                
## [49] "professor"            "project"              "weird"               
## 
## $x$freq
##  [1]  3  3  2  5  2  2  2  3  2  2  3  5  4  2  9  4  2  9 11  2  2  2 19 14  3
## [26]  3  5  6  2  2  2 17  3  4 20  8  2  2  6  2  2  2  2  2  3  5  3  2  3  2
## [51]  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 86. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.11.2 Don’t Belong

## $x
## $x$word
## [1] "art student"          "architecture student" "building"            
## [4] "major"                "time"                
## 
## $x$freq
## [1] 2 2 3 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 60
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.12 Library

6.2.1.12.1 Belong

## $x
## $x$word
##   [1] "front desk"        "fourth floor"      "same reason"      
##   [4] "good environment"  "study environment" "study room"       
##   [7] "wide variety"      "good place"        "many place"       
##  [10] "quiet area"        "same goal"         "study space"      
##  [13] "fantastic place"   "favorite place"    "few place"        
##  [16] "finding place"     "great experience"  "same mindset"     
##  [19] "study group"       "noise level"       "quiet environment"
##  [22] "quiet spaces"      "quiet section"     "same thing"       
##  [25] "most student"      "most part"         "good atmosphere"  
##  [28] "own business"      "fellow student"    "own space"        
##  [31] "great place"       "common goal"       "safe environment" 
##  [34] "quiet place"       "tutoring center"   "other student"    
##  [37] "own thing"         "many resource"     "poetry class"     
##  [40] "quiet space"       "many hour"         "silent place"     
##  [43] "easy access"       "nice place"        "many people"      
##  [46] "open space"        "group project"     "most people"      
##  [49] "quiet corner"      "nice quiet"        "minde people"     
##  [52] "studious person"   "quiet atmosphere"  "comforting place" 
##  [55] "easy place"        "science library"   "other people"     
##  [58] "area"              "own work"          "work do"          
##  [61] "tutor"             "good"              "academic"         
##  [64] "comfortable place" "study"             "same"             
##  [67] "other friend"      "comfortable space" "environment"      
##  [70] "experience"        "spot"              "room"             
##  [73] "knight"            "own"               "great"            
##  [76] "business"          "goal"              "person"           
##  [79] "pressure"          "similar"           "school work"      
##  [82] "space"             "quiet"             "free"             
##  [85] "neutral"           "night"             "library staff"    
##  [88] "group"             "community"         "project"          
##  [91] "thing"             "student"           "need"             
##  [94] "open"              "part"              "silent"           
##  [97] "week"              "best"              "nice"             
## [100] "welcoming"         "atmosphere"        "math"             
## [103] "safe"              "wonderful"         "tutoring"         
## [106] "peaceful"          "studious"          "class"            
## [109] "comforting"        "computer"          "general"          
## [112] "relaxed"           "school"            "easy"             
## [115] "resource"          "time"              "staff"            
## [118] "building"          "hour"              "available"        
## [121] "calm"              "people"            "friendly"         
## [124] "attention"         "cafe"              "employee"         
## [127] "exam"              "feeling"           "kid"              
## [130] "location"          "productive"        "professor"        
## [133] "public"            "service"           "stuff"            
## [136] "such"              "type"              "understanding"    
## [139] "way"               "year"              "work"             
## [142] "help"              "crowd"             "distraction"      
## [145] "perfect"           "talk"              "comfortable"      
## [148] "helpful"           "privacy"           "sense"            
## [151] "job"               "friend"            "welcome"          
## [154] "librarian"         "book"              "question"         
## [157] "alone"             "one"               "homework"         
## [160] "campus"            "ability"           "able"             
## [163] "academics"         "anxiety"           "architecture"     
## [166] "assignment"        "basement"          "bunch"            
## [169] "busy"              "classmate"         "comforte"         
## [172] "connect"           "coworker"          "day"              
## [175] "degree"            "don"               "ease"             
## [178] "education"         "else"              "final"            
## [181] "focus"             "full"              "hard"             
## [184] "home"              "independent"       "judgement"        
## [187] "kind"              "knowledge"         "layout"           
## [190] "meet"              "name"              "odd"              
## [193] "okay"              "option"            "past"             
## [196] "peace"             "plenty"            "presence"         
## [199] "quietness"         "research"          "respectful"       
## [202] "roommate"          "rude"              "spacious"         
## [205] "stack"             "stress"            "supportive"       
## [208] "teacher"           "test"              "thought"          
## [211] "ton"               "top"               "uncomfortable"    
## [214] "university"        "uo"                "useful"           
## [217] "vibe"              "wealth"            "willing"          
## [220] "worker"            "world"            
## 
## $x$freq
##   [1]  2  6  4  2  2  7  2 13  3  3  7  3  2  4  2  2  2  2  4  2  2  2  2  6  2
##  [26]  5  2  8  3  3 19  3  3 21  3 13 14  2  2  4  3  2  2 10  3  2  4  4  2  3
##  [51]  2  3  2  2  4  2  7  6  2  7  4  4  2  6 21  4  2  3  2  3  2  9  4  5  6
##  [76]  2  4  4  3  3  5 25 71  2  2  5  2  9  4  3 16 29  4  8  3  3  2  4 41  6
## [101] 10  3 12  2  6  6  5 15  2  5  2  2  6 13 10 29 17  8  7  4 11 83 13  2  8
## [126]  2  2  2  2  2  4  2  2  4  2  2  4  2  6  6 56 16  3  6  3  3 37 25  4  4
## [151]  5 29 12  7 25  9 11 26 40 15  2 17  5  2  2  3  2  3  3  4  3  3  3  8  2
## [176]  2  3  7 17  2  3  3  4  8  3  2  7  2  2  2  2  2  3  2  2  6  3  2  2  2
## [201] 13  2  2  2  2  2  3  2  2  2  2  2  4  5  2  3  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 2.168675
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 663 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.12.2 Don’t Belong

## $x
## $x$word
##  [1] "group project"     "imposter syndrome" "many people"      
##  [4] "first year"        "science library"   "quiet environment"
##  [7] "homeless people"   "background noise"  "room"             
## [10] "other people"      "study"             "big"              
## [13] "little"            "library people"    "enough"           
## [16] "scary"             "student"           "atmosphere"       
## [19] "bathroom"          "area"              "work"             
## [22] "building"          "people"            "person"           
## [25] "time"              "chair"             "money"            
## [28] "noise"             "staff"             "vibe"             
## [31] "wrong"             "quiet"             "lack"             
## [34] "computer"          "layout"            "lost"             
## [37] "resource"          "thing"             "way"              
## [40] "weird"             "reason"            "comfortable"      
## [43] "feeling"           "smart"             "ability"          
## [46] "able"              "attention"         "cafe"             
## [49] "campus"            "cold"              "comparison"       
## [52] "covid"             "discomfort"        "energy"           
## [55] "familiar"          "feel"              "freshman"         
## [58] "friendly"          "hard"              "help"             
## [61] "intimidat"         "intimidating"      "kind"             
## [64] "large"             "odd"               "order"            
## [67] "overwhelming"      "peer"              "prison"           
## [70] "question"          "silence"           "strange"          
## [73] "studious"          "sure"              "talk"             
## [76] "uncomfortable"     "unsure"            "welcome"          
## [79] "worried"          
## 
## $x$freq
##  [1]  2  2  2  2 10  2  3  3  2  3  3  3  2  2  2  3 10  4  2  2  3  6 28  3 11
## [26]  2  2  6  2  2  2 26  6  3  3  3  6  3  6  3  4  9  5  7  2  3  2  2  3  2
## [51]  2  2  2  2  2  2  2  3 12  8  2  3  3  2  2  3  2  3  2  2  2  2  4  3  3
## [76]  7  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 6.428571
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 207. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.13 Lillis Business Complex

6.2.1.13.1 Belong

## $x
## $x$word
##  [1] "other student"       "business fraternity" "business student"   
##  [4] "direct admit"        "lundquist college"   "familiar face"      
##  [7] "business major"      "business school"     "accounting major"   
## [10] "same major"          "coffee shop"         "school work"        
## [13] "open space"          "many friend"         "same thing"         
## [16] "business class"      "many class"          "great place"        
## [19] "first class"         "many people"         "business building"  
## [22] "beautiful building"  "favorite building"   "club"               
## [25] "group"               "study"               "business"           
## [28] "college"             "open"                "lillis complex"     
## [31] "student"             "major"               "great"              
## [34] "resource"            "school"              "nice place"         
## [37] "event"               "complex"             "advisor"            
## [40] "part"                "friendly"            "member"             
## [43] "thing"               "friend"              "class"              
## [46] "day"                 "lcb"                 "lilli"              
## [49] "peer"                "year"                "people"             
## [52] "building"            "atmosphere"          "community"          
## [55] "connection"          "easy"                "welcome"            
## [58] "window"              "nice"                "professor"          
## [61] "staff"               "home"                "way"                
## [64] "welcoming"           "time"                "comfortable"        
## [67] "activity"            "akpsi"               "cafe"               
## [70] "campus"              "classmate"           "connect"            
## [73] "conversation"        "feeling"             "happy"              
## [76] "help"                "helpful"             "homework"           
## [79] "involved"            "lilis"               "majority"           
## [82] "minor"               "productive"          "sense"              
## [85] "sort"                "table"               "teacher"            
## [88] "term"                "ton"                
## 
## $x$freq
##  [1]  3  3 13  2  2  2 27 11  4  2  3  2  2  2  2  3  2  4  2  2  3  2  2  3  2
## [26]  2 12  2  2  2  6 15  3  4  5  2  2  3  3  6  2  3  2 13 43  5  2  2  2  4
## [51] 33 27  3  3  3  3  3  3  7  7  4  5  5  5 21 14  3  2  4  4  5  2  2  2  2
## [76]  2  5  2  3  2  8  2  2  4  2  2  4  3  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 4.186047
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 197 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.13.2 Don’t Belong

## $x
## $x$word
##   [1] "business kid"         "greek life"           "business major"      
##   [4] "business majors"      "bus major"            "other major"         
##   [7] "business school"      "business student"     "business minor"      
##  [10] "science major"        "general atmosphere"   "little uncomfortable"
##  [13] "different major"      "many people"          "few class"           
##  [16] "business people"      "weird vibe"           "most people"         
##  [19] "other people"         "business class"       "business building"   
##  [22] "group"                "business"             "major"               
##  [25] "community"            "desk"                 "type"                
##  [28] "complex"              "vibe"                 "school"              
##  [31] "student"              "environment"          "person"              
##  [34] "math"                 "serious"              "uncomfortable"       
##  [37] "different"            "interest"             "related"             
##  [40] "weird"                "best"                 "big"                 
##  [43] "busy"                 "nice"                 "question"            
##  [46] "people"               "space"                "anxiety"             
##  [49] "college"              "department"           "exclusive"           
##  [52] "experience"           "large"                "odd"                 
##  [55] "reason"               "same"                 "spot"                
##  [58] "unwelcoming"          "class"                "intimidating"        
##  [61] "building"             "open"                 "outsider"            
##  [64] "campus"               "hard"                 "time"                
##  [67] "full"                 "bunch"                "classroom"           
##  [70] "comfortable"          "conversation"         "course"              
##  [73] "crowd"                "else"                 "expensive"           
##  [76] "fact"                 "faculty"              "familiar"            
##  [79] "friendly"             "idea"                 "inclusive"           
##  [82] "intimidat"            "kind"                 "lack"                
##  [85] "less"                 "lilli"                "loud"                
##  [88] "money"                "nicer"                "one"                 
##  [91] "opportunity"          "part"                 "past"                
##  [94] "rude"                 "scary"                "sense"               
##  [97] "stare"                "suits"                "sure"                
## [100] "way"                  "welcome"              "world"               
## 
## $x$freq
##   [1]  2  5 62  5  2  2 17 23  3  2  2  2  2  5  4  4  2  3  2  2  2  2 19 10  2
##  [26]  2  3  2  2  4 15  3  2  2  2  4  4  3  2  2  2  2  5  2  2 48  7  2  4  2
##  [51]  2  2  2  2  2  2  2  2 34  5 42  3  3  4  4 17  8  2  3  8  2  2  2  3  2
##  [76]  2  3  2  2  3  2  5  3  2  2  3  6  2  2  3  2  6  2  2  2  2  2  2  2  3
## [101]  5  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 2.903226
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 263 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.14 Lokey Science Complex

6.2.1.14.1 Overall Belong

## $x
## $x$word
##   [1] "good experience"    "office hour"        "science major"     
##   [4] "science complex"    "stem major"         "science decoration"
##   [7] "science majors"     "similar interest"   "biology major"     
##  [10] "bulletin boards"    "large lecture"      "science library"   
##  [13] "great place"        "physic major"       "general area"      
##  [16] "good place"         "stem community"     "chemistry major"   
##  [19] "teach space"        "science student"    "favorite place"    
##  [22] "science building"   "similar thing"      "chemistry lecture" 
##  [25] "coffee shop"        "science class"      "other student"     
##  [28] "major class"        "freshman year"      "similar class"     
##  [31] "biology lab"        "multiple class"     "knight library"    
##  [34] "nice place"         "chem lab"           "much time"         
##  [37] "spend time"         "other people"       "many class"        
##  [40] "study"              "experience"         "chem class"        
##  [43] "chemistry lab"      "other friend"       "group"             
##  [46] "many people"        "science"            "chemistry class"   
##  [49] "major"              "research lab"       "area"              
##  [52] "similar"            "willamette hall"    "interest"          
##  [55] "office"             "best friend"        "professor"         
##  [58] "space"              "general"            "nice"              
##  [61] "library"            "community"          "hall"              
##  [64] "own"                "most time"          "environment"       
##  [67] "chemistry"          "college"            "help"              
##  [70] "knight"             "open"               "thing"             
##  [73] "quiet"              "room"               "student"           
##  [76] "building"           "resource"           "lab"               
##  [79] "research"           "year"               "cool"              
##  [82] "class"              "work"               "time"              
##  [85] "atmosphere"         "cafe"               "staff"             
##  [88] "university"         "people"             "willamette"        
##  [91] "comfortable"        "familiar"           "inclusive"         
##  [94] "friend"             "friendly"           "welcoming"         
##  [97] "home"               "klamath"            "part"              
## [100] "able"               "amazing"            "atrium"            
## [103] "basement"           "campus"             "classmate"         
## [106] "columbia"           "connect"            "crowd"             
## [109] "day"                "element"            "emu"               
## [112] "helpful"            "homework"           "huestis"           
## [115] "interested"         "job"                "life"              
## [118] "majority"           "peer"               "plenty"            
## [121] "reason"             "schoolwork"         "setting"           
## [124] "silent"             "team"               "term"              
## [127] "topic"              "uo"                 "way"               
## 
## $x$freq
##   [1]  3  4 15  9 12  2  2  5  3  2  2 29 10  2  2  2  2  2  2  2  5  7  2  2  2
##  [26]  5  2  2  3  2  2  3  3  2  2  2  2  4  6  5  2  2  2  2  3  2  5  2 10  4
##  [51]  3  2  3  4  4  2  2  5  2  7 12  3  4  2  2  5  4  2  3  2  3  2  7  3 11
##  [76] 23  4 20  6  6  2 52 13 25  7  2  2  2 50 14 19  3  3 37  4  5 11  9 10  3
## [101]  2  3  2 10  3  7  4  2  3  2  2  3  7  3  3  4  2  3  5  2  2  2  2  2  2
## [126]  2  2  2  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 3.461538
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 299(n_Invalid = 5 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 207 students provided responses regarding one place, n = 35 provided responses regarding two places, n = 6 provided responses regarding three places, and n = 1 provided responses regarding four places within the Lokey Complex. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.14.2 Overall Don’t Belong

## $x
## $x$word
##  [1] "science complex"  "chemistry lab"    "other student"    "only person"     
##  [5] "comfort zone"     "chemistry class"  "science major"    "science person"  
##  [9] "fellow student"   "graduate student" "science student"  "science library" 
## [13] "chem lab"         "stem major"       "less time"        "most part"       
## [17] "science class"    "smart enough"     "science people"   "science building"
## [21] "experience"       "science"          "type"             "major"           
## [25] "student"          "lab"              "professor"        "time"            
## [29] "reason"           "research"         "smart"            "good"            
## [33] "class"            "people"           "area"             "building"        
## [37] "biology"          "exclusive"        "hard"             "year"            
## [41] "crowd"            "hall"             "lecture"          "male"            
## [45] "material"         "pacific"          "part"             "smarter"         
## [49] "thing"            "way"              "best"             "sciences"        
## [53] "comfortable"      "difficult"        "able"             "campus"          
## [57] "cinema"           "columbia"         "doctor"           "dumb"            
## [61] "easy"             "else"             "facility"         "faculty"         
## [65] "failure"          "friend"           "goal"             "idea"            
## [69] "inferior"         "intimidat"        "klamath"          "large"           
## [73] "need"             "open"             "outsider"         "possible"        
## [77] "problem"          "program"          "sound"            "suck"            
## [81] "uncomfortable"    "uo"               "willamette"       "work"            
## 
## $x$freq
##  [1]  3  2  2  2  2  3 18  3  2  2  8  6  3  6  2  2  5  3  2 11  2 16  2 15 11
## [26]  3  3  3  2  2  4  3 20 15  5 32  3  3  3  3  2  2  2  2  2  2  4  2  5  5
## [51]  3  3  4  4  2  2  3  2  4  3  2  3  2  3  2  5  2  5  3  3  3  2  3  2  2
## [76]  2  2  2  2  2  3  2  7  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 5.625
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 175 (n_Invalid = 7 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 207 students provided responses regarding one place, n = 35 provided responses regarding two places, n = 6 provided responses regarding three places, and n = 1 provided responses regarding four places within the Lokey Complex. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.14.3 Columbia

6.2.1.14.3.1 Belong

## $x
## $x$word
##  [1] "large lecture"     "chemistry lecture" "many class"       
##  [4] "multiple class"    "major"             "people"           
##  [7] "class"             "student"           "friend"           
## [10] "building"          "comfortable"       "familiar"         
## [13] "room"             
## 
## $x$freq
##  [1]  2  2  3  2  2  3 17  2  5  5  2  2  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 10.58824
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.14.4 Klamath

6.2.1.14.4.1 Belong

## $x
## $x$word
##  [1] "biology major"    "science complex"  "science library"  "science building"
##  [5] "chemistry lab"    "library"          "building"         "lab"             
##  [9] "class"            "time"             "people"           "campus"          
## [13] "comfortable"      "interested"       "part"             "peer"            
## [17] "resource"         "setting"         
## 
## $x$freq
##  [1] 2 4 7 4 2 2 4 5 5 6 8 2 5 2 3 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.4.2 Don’t Belong

## $x
## $x$word
## [1] "science major"   "science student" "chem lab"        "science library"
## [5] "building"        "doctor"          "dumb"            "intimidat"      
## 
## $x$freq
## [1] 3 4 3 3 4 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 45
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.5 Lewis

6.2.1.14.5.1 Belong

## $x
## $x$word
##  [1] "research lab" "work"         "lab"          "research"     "student"     
##  [6] "building"     "friend"       "home"         "homework"     "part"        
## [11] "team"        
## 
## $x$freq
##  [1] 3 2 4 4 2 5 4 3 3 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 36
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.5.2 Don’t Belong

## $x
## $x$word
## [1] "less time"        "science major"    "graduate student" "science"         
## [5] "student"          "building"         "people"           "way"             
## 
## $x$freq
## [1] 2 7 2 4 2 8 6 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.6 Science Commons

6.2.1.14.6.1 Belong

## $x
## $x$word
##  [1] "science major"  "stem major"     "science majors" "great place"   
##  [5] "freshman year"  "good place"     "favorite place" "stem community"
##  [9] "coffee shop"    "similar thing"  "similar class"  "knight library"
## [13] "major"          "science"        "study"          "building"      
## [17] "nice"           "resource"       "group"          "library"       
## [21] "class"          "comfortable"    "knight"         "quiet"         
## [25] "student"        "environment"    "work"           "people"        
## [29] "friendly"       "home"           "time"           "atmosphere"    
## [33] "friend"         "able"           "amazing"        "campus"        
## [37] "classmate"      "day"            "emu"            "peer"          
## [41] "plenty"         "welcoming"     
## 
## $x$freq
##  [1]  8  9  2  7  2  2  3  2  2  2  2  2  2  2  2  2  5  2  2  9  6  5  2  5  4
## [26]  3  6 19  2  3  7  4 17  2  2  4  3  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9.473684
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.14.7 Willamette

6.2.1.14.7.1 Belong

## $x
## $x$word
##  [1] "office hour"        "science major"      "science complex"   
##  [4] "science decoration" "chem lab"           "physic major"      
##  [7] "science library"    "great place"        "science building"  
## [10] "science class"      "major"              "area"              
## [13] "many class"         "atmosphere"         "open"              
## [16] "building"           "class"              "home"              
## [19] "time"               "year"               "friend"            
## [22] "people"             "comfortable"        "atrium"            
## [25] "campus"             "homework"           "interest"          
## [28] "job"                "part"               "student"           
## 
## $x$freq
##  [1]  2  6  2  2  2  2  2  3  2  2  2  2  2  3  3  6 19  2  6  2  9 12  5  3  2
## [26]  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9.473684
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.14.7.2 Don’t Belong

## $x
## $x$word
##  [1] "science complex"  "science person"   "science major"    "stem major"      
##  [5] "science student"  "science building" "science class"    "science"         
##  [9] "major"            "people"           "smart"            "student"         
## [13] "building"         "time"             "class"            "way"             
## [17] "able"             "doctor"           "good"             "idea"            
## [21] "inferior"         "outsider"         "problem"          "sound"           
## [25] "work"            
## 
## $x$freq
##  [1] 2 2 5 3 3 4 2 6 6 5 2 3 8 2 8 2 2 2 2 3 2 2 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.15 Matthew Knight Arena

6.2.1.15.1 Belong

## $x
## $x$word
##  [1] "basketball game" "matt knight"     "student section" "school spirit"  
##  [5] "basketball"      "good time"       "sport team"      "much fun"       
##  [9] "student"         "game"            "team"            "people"         
## [13] "event"           "time"            "school"          "sport"          
## [17] "atmosphere"      "duck"            "fun"             "friend"         
## [21] "man"             "part"           
## 
## $x$freq
##  [1]  5  5  3  2  4  2  2  3  2  9  3  2  2  2  3  9  2  4 12  9  2  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 15
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 47. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.15.2 Don’t Belong

## $x
## $x$word
##  [1] "sport person"    "greek life"      "big"             "student section"
##  [5] "weird"           "sport fan"       "event"           "basketball"     
##  [9] "sport game"      "student"         "game"            "people"         
## [13] "best"            "crowd"           "sport"           "campus"         
## [17] "part"            "time"            "arena"           "athlete"        
## [21] "friend"          "fun"             "interested"      "location"       
## [25] "moment"          "peer"            "uo"             
## 
## $x$freq
##  [1]  2  2  2  2  2  2  3  3  2  6  9  4  2  2 23  2  2  2  2  2  2  2  3  2  2
## [26]  2  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 7.826087
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 66 (n_Invalid = 4 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.16 McKenzie

6.2.1.16.1 Belong

## $x
## $x$word
##  [1] "history major" "history class" "many class"    "several class"
##  [5] "comfortable"   "class"         "helpful"       "people"       
##  [9] "professor"     "building"      "nice"          "staff"        
## [13] "time"         
## 
## $x$freq
##  [1] 5 2 2 2 2 7 2 2 4 8 3 3 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 29 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.16.2 Don’t Belong

6.2.1.17 Oregon

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.17.1 Belong

## $x
## $x$word
##  [1] "academic advising"   "traditional student" "great job"          
##  [4] "pathwayoregon"       "office"              "student"            
##  [7] "advisor"             "hall"                "community"          
## [10] "space"               "welcoming"           "job"                
## [13] "building"            "helpful"             "cmae"               
## [16] "people"              "ability"             "aec"                
## [19] "best"                "center"              "comfortable"        
## [22] "dean"                "friendly"            "help"               
## [25] "homework"            "nice"                "uo"                 
## [28] "willing"            
## 
## $x$freq
##  [1]  2  3  2  2  4  5  2  2  2  2  2  4  4  2 13  7  2  2  2  2  4  3  2  3  2
## [26]  3  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 13.84615
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 33. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.17.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.18 Straub

6.2.1.18.1 Belong

## $x
## $x$word
##  [1] "good memory"           "office hour"           "psychology major"     
##  [4] "similar interest"      "many people"           "psychology department"
##  [7] "major"                 "psychology"            "professor"            
## [10] "people"                "class"                 "comfortable"          
## [13] "student"               "nice"                  "building"             
## [16] "time"                  "event"                 "friend"               
## [19] "helpful"               "home"                  "majority"             
## [22] "study"                 "year"                 
## 
## $x$freq
##  [1]  2  2 17  2  2  2  4  5  2  5 21  2  2  5 15 10  2  4  2  3  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 8.571429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 56. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.18.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.19 Student Rec Complex

6.2.1.19.1 Belong

## $x
## $x$word
##   [1] "womens hour"            "judgement zone"         "ultimate frisbee"      
##   [4] "self improvement"       "many class"             "similar goal"          
##   [7] "positive experience"    "team"                   "many other"            
##  [10] "duck store"             "mental health"          "same goal"             
##  [13] "own business"           "own pace"               "yoga class"            
##  [16] "free time"              "athletic person"        "pe class"              
##  [19] "pema class"             "woman hour"             "winter term"           
##  [22] "many people"            "good environment"       "rock climbing"         
##  [25] "rock wall"              "many way"               "favorite place"        
##  [28] "great place"            "safe space"             "similar interest"      
##  [31] "woman block"            "own thing"              "active person"         
##  [34] "familiar face"          "weight lifting"         "safe place"            
##  [37] "same reason"            "whole life"             "co worker"             
##  [40] "practice"               "basketball court"       "same thing"            
##  [43] "great way"              "inviting atmosphere"    "good exercise"         
##  [46] "other student"          "little bit"             "spend time"            
##  [49] "exercise class"         "free"                   "good place"            
##  [52] "bad experience"         "daily routine"          "student worker"        
##  [55] "good time"              "self"                   "turf field"            
##  [58] "freshman year"          "other place"            "uo"                    
##  [61] "positive"               "welcoming environment"  "stress relief"         
##  [64] "relieve stress"         "fitness class"          "rec center"            
##  [67] "great"                  "rec everyday"           "fitness community"     
##  [70] "other people"           "yoga"                   "goal"                  
##  [73] "fun place"              "center"                 "course"                
##  [76] "guy"                    "morning"                "such"                  
##  [79] "own"                    "other gym"              "group"                 
##  [82] "activity"               "hour"                   "judgement"             
##  [85] "woman"                  "most people"            "good"                  
##  [88] "environment"            "physical"               "amazing"               
##  [91] "experience"             "intramural"             "lifting"               
##  [94] "same"                   "building"               "level"                 
##  [97] "swim"                   "field"                  "tennis"                
## [100] "class"                  "student"                "weight"                
## [103] "health"                 "area"                   "athletic"              
## [106] "new"                    "reason"                 "community"             
## [109] "individual"             "lift"                   "rock"                  
## [112] "nice place"             "thing"                  "feel"                  
## [115] "comfortable place"      "interest"               "part"                  
## [118] "body"                   "event"                  "familiar"              
## [121] "head"                   "exercise"               "comfortable exercising"
## [124] "space"                  "best"                   "confidence"            
## [127] "worker"                 "atmosphere"             "bad"                   
## [130] "sport"                  "active"                 "fun"                   
## [133] "year"                   "healthy"                "bit"                   
## [136] "equipment"              "exercising"             "incredible"            
## [139] "open"                   "studio"                 "turf"                  
## [142] "time"                   "better"                 "people"                
## [145] "employee"               "school"                 "way"                   
## [148] "fitness"                "judgment"               "sure"                  
## [151] "welcoming"              "available"              "facility"              
## [154] "fall"                   "fear"                   "girl"                  
## [157] "hobby"                  "important"              "peer"                  
## [160] "pickup"                 "shape"                  "strong"                
## [163] "teammate"               "weird"                  "basketball"            
## [166] "kind"                   "life"                   "soccer"                
## [169] "supportive"             "game"                   "happy"                 
## [172] "instructor"             "job"                    "gym"                   
## [175] "ability"                "stress"                 "addition"              
## [178] "judgemental"            "work"                   "nice"                  
## [181] "staff"                  "welcome"                "energy"                
## [184] "comfortable"            "home"                   "one"                   
## [187] "week"                   "else"                   "mind"                  
## [190] "friend"                 "respectful"             "confident"             
## [193] "day"                    "friendly"               "able"                  
## [196] "afraid"                 "apart"                  "attention"             
## [199] "big"                    "campus"                 "care"                  
## [202] "classmate"              "clean"                  "college"               
## [205] "connect"                "conversation"           "coworker"              
## [208] "door"                   "easy"                   "effort"                
## [211] "enthusiastic"           "expectation"            "form"                  
## [214] "general"                "hard"                   "help"                  
## [217] "helpful"                "inclusive"              "interested"            
## [220] "intimidat"              "issue"                  "location"              
## [223] "love"                   "machine"                "mix"                   
## [226] "music"                  "nervous"                "opportunity"           
## [229] "order"                  "outlet"                 "pool"                  
## [232] "purpose"                "respect"                "result"                
## [235] "rude"                   "service"                "shoulders"             
## [238] "size"                   "strength"               "stuff"                 
## [241] "teacher"                "ton"                    "training"              
## [244] "understanding"          "use"                    "willing"               
## 
## $x$freq
##   [1]  2  2  2  3  2  5  4  3  3  2  4  4  7  2  2  2  2 12  2 13  2  6  2  4  7
##  [26]  2  6 11  4  5  3 11  3  3  2  3  5  2  2  2  5  2  3  2  2 11  2  2  6  2
##  [51]  3  4  2  3  8  3  2  3  2  4  2  2  2  2  4 14  5  2  2 15  2  2  5  2  2
##  [76]  5  3  2  3  2  6  5  4  6  7  2 12  4  2  3  4  2  3  3  4  2  2  4  7 40
## [101] 12  9  4  4  3  3  3  9  2  2  4  3  8  5  3  3  6  5  2  2  2 28  2 13  4
## [126]  3  4  3  3 22  6 27  8 11  2  7  3  2  5  2  2 39  9 97  4  4 13 19  3  4
## [151] 11  2  6  2  2  4  2  2  2  2  7  4  2  2 30  5 10 10  6  3  7 10  3 44  7
## [176] 18  4  4  8 36 23 10  5 44  6 18 12  9  9 85 10 12 33 19 15  2  2  2  2 12
## [201]  3  2  2  2  7  2  2  3  7  3  2  2  2  2  2  5 12  3  3  2  2  2  2  6  2
## [226]  3  2  6  3  4  3  3  2  2  3  2  2  2  3  2  4  5  3  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 1.85567
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 692 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.19.2 Don’t Belong

## $x
## $x$word
##   [1] "personal issue"           "physical limitation"     
##   [3] "recreation center"        "self conscience"         
##   [5] "health issue"             "personal problem"        
##   [7] "woman hour"               "pe class"                
##   [9] "locker room"              "weight room"             
##  [11] "fitness culture"          "transfer student"        
##  [13] "few time"                 "many people"             
##  [15] "certain way"              "same interest"           
##  [17] "self conscious"           "certain area"            
##  [19] "athletic enough"          "toxic environment"       
##  [21] "skill level"              "athletic person"         
##  [23] "rec center"               "other student"           
##  [25] "little intimidating"      "gym culture"             
##  [27] "intimidating environment" "social anxiety"          
##  [29] "more help"                "fat person"              
##  [31] "only time"                "most day"                
##  [33] "athletic type"            "athletic situation"      
##  [35] "student rec"              "hour"                    
##  [37] "most people"              "gender"                  
##  [39] "image"                    "culture"                 
##  [41] "athletic ability"         "worried people"          
##  [43] "weight area"              "competitive"             
##  [45] "enough"                   "muscular"                
##  [47] "overweight"               "own"                     
##  [49] "schedule"                 "athletic people"         
##  [51] "other people"             "class"                   
##  [53] "intimidating place"       "student"                 
##  [55] "person"                   "exercise"                
##  [57] "athlete"                  "hard time"               
##  [59] "bit"                      "fitness"                 
##  [61] "inclusive"                "little"                  
##  [63] "environment"              "unfit people"            
##  [65] "woman"                    "bigger"                  
##  [67] "campus"                   "uncomfortable experience"
##  [69] "good"                     "different"               
##  [71] "intimidating"             "type"                    
##  [73] "body"                     "appearance"              
##  [75] "girl"                     "helpful"                 
##  [77] "new"                      "same"                    
##  [79] "bad"                      "reason"                  
##  [81] "athletic"                 "group"                   
##  [83] "thing"                    "feeling"                 
##  [85] "rude"                     "idea"                    
##  [87] "male"                     "tennis"                  
##  [89] "space"                    "way"                     
##  [91] "equipment"                "area"                    
##  [93] "time"                     "confident"               
##  [95] "crowd"                    "day"                     
##  [97] "exercising"               "experience"              
##  [99] "eye"                      "fat"                     
## [101] "field"                    "general"                 
## [103] "interested"               "locker"                  
## [105] "nice"                     "one"                     
## [107] "overwhelming"             "term"                    
## [109] "vibe"                     "weight"                  
## [111] "machine"                  "anxiety"                 
## [113] "shape"                    "ability"                 
## [115] "big"                      "facility"                
## [117] "kind"                     "sport"                   
## [119] "afraid"                   "easier"                  
## [121] "stare"                    "unfit"                   
## [123] "conscious"                "people"                  
## [125] "gym"                      "amount"                  
## [127] "attention"                "backpack"                
## [129] "comment"                  "else"                    
## [131] "female"                   "judge"                   
## [133] "large"                    "less"                    
## [135] "lift"                     "muscle"                  
## [137] "sort"                     "weights"                 
## [139] "weird"                    "wrong"                   
## [141] "year"                     "guy"                     
## [143] "man"                      "scary"                   
## [145] "hard"                     "active"                  
## [147] "atmosphere"               "best"                    
## [149] "confidence"               "fault"                   
## [151] "front"                    "full"                    
## [153] "head"                     "insecure"                
## [155] "majority"                 "pressure"                
## [157] "safe"                     "sense"                   
## [159] "staff"                    "strong"                  
## [161] "worker"                   "uncomfortable"           
## [163] "friend"                   "judgemental"             
## [165] "welcoming"                "beginner"                
## [167] "knowledge"                "nervous"                 
## [169] "old"                      "school"                  
## [171] "anxious"                  "healthy"                 
## [173] "money"                    "public"                  
## [175] "judgmental"               "skinny"                  
## [177] "lack"                     "building"                
## [179] "comfortable"              "able"                    
## [181] "activity"                 "age"                     
## [183] "available"                "boy"                     
## [185] "busy"                     "care"                    
## [187] "case"                     "clothes"                 
## [189] "color"                    "common"                  
## [191] "community"                "difficult"               
## [193] "don"                      "easy"                    
## [195] "embarrased"               "example"                 
## [197] "fact"                     "familiar"                
## [199] "fee"                      "fine"                    
## [201] "fool"                     "friendly"                
## [203] "funny"                    "inconvenient"            
## [205] "instructor"               "intimidat"               
## [207] "intimidate"               "intimidated"             
## [209] "involved"                 "judgement"               
## [211] "judgment"                 "morning"                 
## [213] "night"                    "odd"                     
## [215] "outsider"                 "overwhelm"               
## [217] "peer"                     "quiet"                   
## [219] "scrawny"                  "short"                   
## [221] "similar"                  "sta"                     
## [223] "stressful"                "stuff"                   
## [225] "stupid"                   "summer"                  
## [227] "sure"                     "treadmill"               
## [229] "trouble"                  "unable"                  
## [231] "university"               "unsure"                  
## [233] "unwelcome"                "uo"                      
## [235] "use"                      "weak"                    
## [237] "welcome"                 
## 
## $x$freq
##   [1]   2   2   2   2   2   2   9   2   2   3   2   2   5  17   4   2   7   3
##  [19]   4   2   2   4  32   4   4   2   2   3   2   2   2   2   2   2   3   2
##  [37]   3   2   2   4   3   2   3   2   2   2   2   2   2   2  19  10   3  16
##  [55]   8  11   6   6   3   4   3   5   4   2  15   2   5   3   5   4   5   7
##  [73]  14   3   2   2   4   3   7   6  24   5   4   3   3   6   4   5  21  10
##  [91]  19   7  27   3   2   3   3  11   2   3   3   5   3   5   2   2   2   2
## [109]   2  18  13  10  15   4   4   5   5   9   3   3   3   3  17 155  81   4
## [127]   2   2   2  10   5   2   2   2   2   2   2   2   4   2   2   9  22   6
## [145]  25   3   3   3   3   3   3   3   3   3   3   3   3   3   6   3   3  36
## [163]  15   7   7   4   4   4   4   4  11   5   5   5   6   7   8  13  26   3
## [181]   2   2   2   2   2   2   2   2   3   2   2   9  13   3   3   2   4   2
## [199]   2   2   2   2   3   2   2   7   5   8   2  10   2   2   5   3   4   2
## [217]   4   2   2   2   3   2   2   2   2   2   8   3   2   3   2   3   3   4
## [235]   3   2   4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 1.16129
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 575 (n_Invalid = 11 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.20 Tykeson

6.2.1.20.1 Belong

## $x
## $x$word
##  [1] "study space"     "good experience" "nice place"      "quiet"          
##  [5] "nice"            "time"            "help"            "building"       
##  [9] "comfortable"     "major"           "work"            "class"          
## [13] "people"          "easy"            "professor"       "welcoming"      
## [17] "atmosphere"      "counselor"       "staff"           "advisor"        
## [21] "ambiance"        "campus"          "classroom"       "friendly"       
## [25] "helpful"         "homework"        "welcome"        
## 
## $x$freq
##  [1]  3  2  2  3  5  2  2  9  3  2  2  5  5  2  2  2  3  3  3 12  2  3  2  2  5
## [26]  3  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 15
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 73 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.20.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.21 University Health Services

6.2.1.21.1 Belong

## $x
## $x$word
##  [1] "health center"      "counseling center"  "counseling service"
##  [4] "counseling"         "service"            "friendly"          
##  [7] "people"             "welcome"            "help"              
## [10] "helpful"            "nice"               "support"           
## [13] "welcoming"         
## 
## $x$freq
##  [1] 2 2 2 2 3 2 2 2 2 3 4 2 4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 45
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 27. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text data were annotated using the udpipe package. Keywords were extracted using the Rapid Keyword Extraction (RAKE) algorithm (Rose et al., 2010). Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket`` palette of theviridis` package.

6.2.1.21.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.22 University Housing

6.2.1.22.1 Overall Belong

## $x
## $x$word
##   [1] "student worker"        "study space"           "study room"           
##   [4] "dining area"           "good experience"       "large group"          
##   [7] "hall government"       "dining hall"           "good memory"          
##  [10] "great experience"      "residence hall"        "hall mate"            
##  [13] "common area"           "great memory"          "great friendhip"      
##  [16] "decent experience"     "many memory"           "earl hall"            
##  [19] "good place"            "great food"            "resident assistant"   
##  [22] "same floor"            "great environment"     "music arc"            
##  [25] "food option"           "first year"            "favorite place"       
##  [28] "best food"             "freshman year"         "last year"            
##  [31] "school year"           "sophomore year"        "whole year"           
##  [34] "good community"        "maker space"           "good friend"          
##  [37] "common room"           "lounge area"           "third floor"          
##  [40] "second floor"          "special place"         "little community"     
##  [43] "study"                 "other back"            "past year"            
##  [46] "amazing memory"        "hamilton dining"       "great community"      
##  [49] "other student"         "carson dining"         "great friend"         
##  [52] "great dorm"            "several friend"        "many friend"          
##  [55] "support system"        "spend time"            "first term"           
##  [58] "art arc"               "same class"            "spring term"          
##  [61] "winter term"           "lifelong friend"       "friend live"          
##  [64] "only friend"           "great people"          "few people"           
##  [67] "dorm hall"             "hamilton hall"         "much fun"             
##  [70] "best friend"           "closest friend"        "many people"          
##  [73] "great time"            "new friend"            "several time"         
##  [76] "carson hall"           "good"                  "club"                 
##  [79] "familiar face"         "strong connection"     "other resident"       
##  [82] "much time"             "barnhart riley"        "dining"               
##  [85] "friend life"           "bean hall"             "welcoming environment"
##  [88] "social"                "friend room"           "close friend"         
##  [91] "second home"           "dorm room"             "fun environment"      
##  [94] "major"                 "strong sense"          "safe space"           
##  [97] "great"                 "friendly staff"        "atmosphere"           
## [100] "area"                  "event"                 "safe place"           
## [103] "other friend"          "other dorm"            "first"                
## [106] "earl"                  "experience"            "freshman"             
## [109] "game"                  "live"                  "such"                 
## [112] "uo"                    "hall"                  "arc"                  
## [115] "student"               "best"                  "group"                
## [118] "closest"               "other people"          "new"                  
## [121] "cool people"           "dorm community"        "nice place"           
## [124] "memory"                "most friend"           "friendhip"            
## [127] "housing"               "music"                 "past"                 
## [130] "food"                  "night"                 "supportive"           
## [133] "college"               "most part"             "year"                 
## [136] "open"                  "staff"                 "life"                 
## [139] "movie"                 "space"                 "amazing"              
## [142] "environment"           "room"                  "close"                
## [145] "floor"                 "wing"                  "bathroom"             
## [148] "energy"                "kind"                  "cool"                 
## [151] "lounge"                "way"                   "resident"             
## [154] "basement"              "week"                  "weird"                
## [157] "art"                   "awesome"               "better"               
## [160] "bond"                  "burgess"               "chill"                
## [163] "interaction"           "love"                  "meal"                 
## [166] "person"                "support"               "community"            
## [169] "term"                  "happy"                 "welcoming"            
## [172] "friend"                "dorm"                  "hamilton"             
## [175] "fun"                   "connection"            "dinner"               
## [178] "full"                  "safe"                  "university"           
## [181] "month"                 "thing"                 "carson"               
## [184] "friendly"              "activity"              "amount"               
## [187] "busy"                  "cashier"               "clean"                
## [190] "day"                   "door"                  "feel"                 
## [193] "layout"                "part"                  "building"             
## [196] "work"                  "people"                "class"                
## [199] "sense"                 "coworker"              "familiar"             
## [202] "boyfriend"             "couple"                "family"               
## [205] "hallway"               "involved"              "neighbor"             
## [208] "time"                  "ra"                    "welcome"              
## [211] "barnhart"              "nice"                  "roommate"             
## [214] "girlfriend"            "inclusive"             "bean"                 
## [217] "unthank"               "kitchen"               "one"                  
## [220] "home"                  "lunch"                 "campus"               
## [223] "comfortable"           "job"                   "helpful"              
## [226] "kalapuya"              "gsh"                   "llc"                  
## [229] "able"                  "access"                "alone"                
## [232] "aspect"                "available"             "bit"                  
## [235] "chance"                "closer"                "coffee"               
## [238] "comforting"            "connect"               "easier"               
## [241] "easy"                  "else"                  "end"                  
## [244] "enjoyable"             "fact"                  "fall"                 
## [247] "fortunate"             "girl"                  "glad"                 
## [250] "grateful"              "hallmate"              "hammy"                
## [253] "hangout"               "heart"                 "hello"                
## [256] "homework"              "homy"                  "identity"             
## [259] "important"             "lovely"                "lucky"                
## [262] "majority"              "moment"                "normal"               
## [265] "nostalgia"             "number"                "outgoing"             
## [268] "partner"               "peace"                 "peer"                 
## [271] "poc"                   "presence"              "problem"              
## [274] "professor"             "reason"                "respectful"           
## [277] "rest"                  "role"                  "roomate"              
## [280] "straub"                "sweet"                 "that"                 
## [283] "tingle"                "transition"            "uncomfortable"        
## [286] "used"                  "walton"               
## 
## $x$freq
##   [1]   2   2   5   6   7   2   8  13   8   2  13   5   3   3   2   2   3   2
##  [19]   4   3   2   2   2   2   2  12   3   2  18   2   3   2   2   2   2  12
##  [37]   3   2   3   2   2   2   2   2   4   2   5   6   5   2   4   2   2  21
##  [55]   2   3   2   3   2   2   4   4   3   3   5   2   4   3   2  30  12   8
##  [73]   3   5   2   3  11   2   3   2   4   2   2   6   2   3   2   2   2  16
##  [91]   4   9   2   2   2   4   7   3   2   2   5   3   5   2   8   3   8   6
## [109]   3   5   2   3  34  12   8   5   5   3   4   2   4   2   2   7   2   3
## [127]   4   3   2  22   2   3   5   5  38   3  11   8   3   9   8   5  23   8
## [145]  34   6   2   2   4   3   5   3   8   2   2   2   3   3   3   2   2   3
## [163]   2   2   3   2   2  52  11   6  12 273 104  39  21  10  10   4  16   3
## [181]   6   5  28  24   2   2   2   2   2   9   2   2   2  14  28   8 161  16
## [199]   5   9   8   3   3  12   3   3   3  71  44  11   7  45  36   4   4  41
## [217]  14   5   5  45   6  25  47   7   9  10  37  25  13   2   6   2   2   2
## [235]   2   2   2   2   9   4   6   6   6   2   2   2   2   3   2   2   4   2
## [253]   2   3   4   6   2   2   2   2   2   8   2   2   3   3   2   3   5   4
## [271]   2   2   5   2   2   2   2   2   3   2   2   2   2   3   6   2  11
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 0.6593407
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 933 (n_Invalid = 7 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 619 students provided responses regarding one place, n = 136 provided responses regarding two places, and n = 14 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.1.22.2 Overall Don’t Belong

## $x
## $x$word
##   [1] "honor college"         "high school"           "first year"           
##   [4] "dining area"           "dining worker"         "international student"
##   [7] "traditional student"   "transfer student"      "overall environment"  
##  [10] "meal plan"             "living experience"     "most student"         
##  [13] "residence hall"        "dining hall"           "bad experience"       
##  [16] "white people"          "greek life"            "common area"          
##  [19] "younger student"       "pac arc"               "many freshmen"        
##  [22] "freshman year"         "huge group"            "rich people"          
##  [25] "college"               "bad vibe"              "many people"          
##  [28] "campus student"        "many friend"           "dorm living"          
##  [31] "freshman live"         "party person"          "social anxiety"       
##  [34] "door open"             "meal point"            "only place"           
##  [37] "dorm life"             "campus life"           "few time"             
##  [40] "other resident"        "other people"          "dining"               
##  [43] "party dorm"            "area"                  "year"                 
##  [46] "different atmosphere"  "expensive dorm"        "student"              
##  [49] "class"                 "location"              "experience"           
##  [52] "great place"           "bad"                   "live"                 
##  [55] "rude people"           "life"                  "couple"               
##  [58] "loud"                  "hall"                  "smart"                
##  [61] "staff"                 "good"                  "party"                
##  [64] "different"             "arc"                   "better"               
##  [67] "great"                 "person"                "side"                 
##  [70] "feeling"               "room"                  "kid"                  
##  [73] "cafeteria"             "close"                 "group"                
##  [76] "connection"            "vibe"                  "community"            
##  [79] "freshman"              "cliquey"               "energy"               
##  [82] "freshmen"              "horrible"              "issue"                
##  [85] "little"                "money"                 "old"                  
##  [88] "rude"                  "space"                 "term"                 
##  [91] "walton"                "carson"                "dorm"                 
##  [94] "atmosphere"            "bit"                   "busy"                 
##  [97] "crowd"                 "earl"                  "nice"                 
## [100] "similar"               "campus"                "hamilton"             
## [103] "night"                 "unthank"               "resident"             
## [106] "people"                "anxiety"               "bathroom"             
## [109] "choice"                "culture"               "dirty"                
## [112] "environment"           "floor"                 "friendhip"            
## [115] "lack"                  "leave"                 "member"               
## [118] "noisy"                 "number"                "roomate"              
## [121] "time"                  "welcoming"             "bean"                 
## [124] "roommate"              "thing"                 "comfortable"          
## [127] "friend"                "girl"                  "point"                
## [130] "weird"                 "difficult"             "hard"                 
## [133] "judgmental"            "neighbor"              "ra"                   
## [136] "reason"                "one"                   "food"                 
## [139] "part"                  "way"                   "full"                 
## [142] "sure"                  "building"              "home"                 
## [145] "uncomfortable"         "don"                   "gsh"                  
## [148] "llc"                   "alone"                 "back"                 
## [151] "background"            "barnhart"              "bunch"                
## [154] "capable"               "chair"                 "chance"               
## [157] "child"                 "crazy"                 "crowded"              
## [160] "dinner"                "diversity"             "elevator"             
## [163] "else"                  "event"                 "fact"                 
## [166] "fancy"                 "friendly"              "fun"                  
## [169] "garbage"               "hallmate"              "hallway"              
## [172] "head"                  "idea"                  "introducktion"        
## [175] "introvert"             "kalapuya"              "kind"                 
## [178] "mess"                  "nervous"               "noise"                
## [181] "obnoxious"             "opportunity"           "overwhelming"         
## [184] "popular"               "presentation"          "prison"               
## [187] "privilege"             "question"              "respectful"           
## [190] "rest"                  "senior"                "sense"                
## [193] "snobby"                "trouble"               "unpleasant"           
## [196] "uo"                    "upperclassman"         "wall"                 
## [199] "wealthy"               "welcome"              
## 
## $x$freq
##   [1]   2   3   5   2   2   2   2   2   2   2   2   2   5  18   6   2   2   2
##  [19]   2   2   2   7   2   3   2   2  10   3   2   2   2   2   2   2   2   2
##  [37]   3   2   4   2   2   2   3   2   8   2   2  16  12   2   7   2   2   3
##  [55]   3   3   3   2  19   2   3   5   3   6   2   2   6   2   2   4  11   7
##  [73]   3   2   9   3   4   9  30   3   2   2   3   2   3   2   6   6   4   2
##  [91]   5   5  65   3   3   3   3   3   4   4  21  12   5   6   7 109   4   2
## [109]   2   2   2   4  14   2   2   2   2   2   2   2  18   2  12  20   7   5
## [127]  43   5   5  12   3  10   3   9  10   3   7   8   8   4   5   5  28   6
## [145]   6  14  19  11   3   3   2   2   3   2   2   2   2   3   2   2   3   2
## [163]   7   2   2   2   8   2   2   3   3   3   2   2   4   3   4   2   4   3
## [181]   2   3   2   2   2   2   2   2   2   4   2   4   2   2   3   3   2   2
## [199]   2   4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 1.651376
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems negatively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 487 (n_Invalid = 10 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 619 students provided responses regarding one place, n = 136 provided responses regarding two places, and n = 14 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the mako palette of the viridis package.

6.2.1.22.3 Barnhart

6.2.1.22.3.1 Belong

## $x
## $x$word
##  [1] "good memory"    "closest friend" "friend"         "roommate"      
##  [5] "people"         "campus"         "floor"          "home"          
##  [9] "nice"           "space"         
## 
## $x$freq
##  [1] 2 2 7 2 2 4 2 2 2 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 25.71429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.22.4 Bean

6.2.1.22.4.1 Belong

## $x
## $x$word
##  [1] "hall government" "first year"      "good experience" "third floor"    
##  [5] "support system"  "lounge area"     "winter term"     "freshman year"  
##  [9] "common room"     "close friend"    "closest friend"  "many friend"    
## [13] "many people"     "good friend"     "second home"     "much time"      
## [17] "arc"             "experience"      "best friend"     "good"           
## [21] "year"            "dorm community"  "dorm room"       "life"           
## [25] "college"         "great"           "memory"          "best"           
## [29] "fun"             "term"            "community"       "room"           
## [33] "building"        "lounge"          "part"            "friend"         
## [37] "social"          "roommate"        "people"          "campus"         
## [41] "home"            "neighbor"        "safe"            "time"           
## [45] "comfortable"     "ra"              "able"            "better"         
## [49] "familiar"        "family"          "friendly"        "hello"          
## [53] "involved"        "kitchen"         "majority"        "month"          
## [57] "movie"           "nice"            "one"             "sense"          
## 
## $x$freq
##  [1]  2  4  2  2  2  2  3  2  2  2  3  4  2  2  2  2  2  2  4  2  5  2  2  2  2
## [26]  2  2  3  2  4 10  6  5  3  3 48  2  5 23  3  6  3  3 14 12 13  2  2  2  3
## [51]  5  2  2  3  2  2  2  8  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 3.75
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.4.2 Don’t Belong

## $x
## $x$word
##  [1] "other resident" "bad"            "friend"         "freshman"      
##  [5] "time"           "comfortable"    "neighbor"       "people"        
##  [9] "capable"        "community"      "don"            "introvert"     
## [13] "noisy"          "prison"         "roommate"       "similar"       
## [17] "uncomfortable"  "vibe"           "weird"         
## 
## $x$freq
##  [1]  2  2  3  2  2  3  4 10  2  2  2  2  2  2  5  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 18
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.5 Carson

6.2.1.22.5.1 Belong

## $x
## $x$word
##  [1] "large group"   "carson dining" "great food"    "few people"   
##  [5] "best friend"   "first year"    "floor"         "year"         
##  [9] "great"         "community"     "good"          "safe"         
## [13] "people"        "friend"        "first"         "comfortable"  
## [17] "staff"         "welcoming"     "campus"        "nice"         
## [21] "resident"      "time"          "ra"            "connection"   
## [25] "helpful"       "home"          "lunch"         "poc"          
## [29] "respectful"    "roommate"      "term"         
## 
## $x$freq
##  [1]  2  2  3  2  4  2  3  4  2  4  3  2 15 18  3  2  2  4  4  4  4  5  6  2  3
## [26]  3  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 10
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.5.2 Don’t Belong

## $x
## $x$word
##  [1] "few time"    "dining hall" "weird"       "great"       "people"     
##  [6] "friend"      "campus"      "floor"       "freshman"    "old"        
## [11] "ra"         
## 
## $x$freq
##  [1] 2 2 2 3 6 4 3 3 2 2 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 30
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.6 Earl

6.2.1.22.6.1 Belong

## $x
## $x$word
##  [1] "best friend"     "closest friend"  "lifelong friend" "community"      
##  [5] "class"           "close"           "time"            "friend"         
##  [9] "fun"             "arc"             "home"            "welcome"        
## [13] "year"            "else"            "floor"           "nice"           
## [17] "people"          "straub"         
## 
## $x$freq
##  [1]  2  2  3  2  3  3  2 12  3  2  2  2  2  2  4  3 14  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 12.85714
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.6.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.1.22.7 Global Scholars

6.2.1.22.7.1 Belong

## $x
## $x$word
##  [1] "dining area"    "dining hall"    "study space"    "common area"   
##  [5] "hall mate"      "nice place"     "event"          "freshman year" 
##  [9] "school year"    "other student"  "familiar face"  "many friend"   
## [13] "friendly staff" "close friend"   "food"           "room"          
## [17] "year"           "nice"           "staff"          "environment"   
## [21] "floor"          "familiar"       "community"      "chill"         
## [25] "friendly"       "roommate"       "friend"         "class"         
## [29] "time"           "happy"          "comfortable"    "home"          
## [33] "people"         "atmosphere"     "awesome"        "building"      
## [37] "campus"         "cashier"        "coworker"       "easier"        
## [41] "fun"            "homework"       "important"      "life"          
## [45] "majority"       "partner"        "safe"           "term"          
## [49] "welcome"       
## 
## $x$freq
##  [1]  3  2  2  2  2  2  2  2  2  2  2  3  2  3  7  4  8  3  3  2  6  3  9  2  6
## [26]  5 51  3 17  4  9  5 21  2  2  3  3  2  5  2  2  3  2  2  3  2  2  2  3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 3.529412
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.7.2 Don’t Belong

## $x
## $x$word
##  [1] "honor college"         "first year"            "freshman year"        
##  [4] "many people"           "international student" "dining area"          
##  [7] "dining hall"           "door open"             "student"              
## [10] "experience"            "freshman"              "smart"                
## [13] "people"                "class"                 "different"            
## [16] "space"                 "anxiety"               "bit"                  
## [19] "person"                "weird"                 "floor"                
## [22] "room"                  "time"                  "friend"               
## [25] "building"              "campus"                "don"                  
## [28] "else"                  "food"                  "friendly"             
## [31] "hamilton"              "nice"                  "opportunity"          
## [34] "part"                  "ra"                    "sense"                
## [37] "uncomfortable"         "welcoming"            
## 
## $x$freq
##  [1]  2  3  3  3  2  2  3  2  8  2  5  2 14  6  3  2  2  2  2  2  3  3  3  7  7
## [26]  5  3  2  2  2  2  3  2  5  3  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 12.85714
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.8 Hamilton

6.2.1.22.8.1 Belong

## $x
## $x$word
##  [1] "same floor"        "art arc"           "dining hall"      
##  [4] "hall government"   "music arc"         "good memory"      
##  [7] "dining area"       "good experience"   "food option"      
## [10] "good friend"       "many friend"       "strong connection"
## [13] "many people"       "first year"        "dorm hall"        
## [16] "great community"   "hamilton dining"   "freshman year"    
## [19] "best friend"       "good"              "other friend"     
## [22] "most part"         "close friend"      "dining"           
## [25] "floor"             "food"              "music"            
## [28] "dinner"            "welcoming"         "housing"          
## [31] "friendly"          "connection"        "experience"       
## [34] "fun"               "amazing"           "space"            
## [37] "wing"              "year"              "burgess"          
## [40] "room"              "community"         "friend"           
## [43] "job"               "sense"             "people"           
## [46] "campus"            "comfortable"       "part"             
## [49] "way"               "building"          "day"              
## [52] "ra"                "roommate"          "time"             
## [55] "home"              "able"              "class"            
## [58] "closer"            "coffee"            "connect"          
## [61] "couple"            "easy"              "energy"           
## [64] "family"            "hammy"             "hangout"          
## [67] "inclusive"         "meal"              "nice"             
## [70] "nostalgia"         "peace"             "resident"         
## [73] "such"              "tingle"            "uncomfortable"    
## [76] "work"             
## 
## $x$freq
##  [1]  2  2  6  2  2  2  3  2  2  2  6  2  2  4  2  3  5  5  7  3  2  2  2  6  3
## [26]  6  3  2  3  3  4  3  3  4  2  2  2 12  2  3 12 50  2  2 32  3  6  6  3  7
## [51]  4 10  5 11 14  4  3  2  2  3  2  3  2  3  2  2  2  2  9  2  2  2  2  2  4
## [76]  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 3.6
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.8.2 Don’t Belong

## $x
## $x$word
##  [1] "dining hall"   "pac arc"       "freshman year" "many people"  
##  [5] "many friend"   "don"           "people"        "freshman"     
##  [9] "one"           "time"          "friend"        "building"     
## [13] "difficult"     "floor"         "good"          "resident"     
## [17] "thing"         "unpleasant"   
## 
## $x$freq
##  [1]  6  2  2  2  2  3 12  4  2  5  6  4  2  3  2  2  3  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 15
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.9 Living Learning

6.2.1.22.9.1 Belong

## $x
## $x$word
##  [1] "past year"       "dining hall"     "many friend"     "great community"
##  [5] "best friend"     "close friend"    "year"            "great"          
##  [9] "hall"            "community"       "staff"           "friend"         
## [13] "memory"          "new"             "floor"           "home"           
## [17] "fun"             "nice"            "people"          "time"           
## [21] "alone"           "building"        "class"           "comfortable"    
## [25] "connect"         "family"          "friendly"        "lunch"          
## [29] "ra"              "roommate"        "safe"            "welcoming"      
## 
## $x$freq
##  [1]  2  2  2  2  4  3  3  2  2  2  2 19  2  2  5  2  3  4 12  5  2  2  2  2  2
## [26]  3  3  2  3  3  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9.473684
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.9.2 Don’t Belong

## $x
## $x$word
##  [1] "most student" "party dorm"   "many people"  "cliquey"      "party"       
##  [6] "freshman"     "roommate"     "time"         "hall"         "people"      
## [11] "class"        "friend"       "building"     "campus"       "different"   
## [16] "girl"        
## 
## $x$freq
##  [1]  2  2  2  2  2  2  3  3  2 16  3  3  2  5  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 11.25
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.10 Kalapuya Ilihi

6.2.1.22.10.1 Belong

## $x
## $x$word
##  [1] "good experience" "maker space"     "great friend"    "good friend"    
##  [5] "close friend"    "best friend"     "dorm hall"       "freshman year"  
##  [9] "floor"           "cool people"     "ra"              "room"           
## [13] "arc"             "community"       "year"            "friend"         
## [17] "freshman"        "people"          "friendly"        "nice"           
## [21] "memory"          "safe"            "art"             "roommate"       
## [25] "time"            "able"            "building"        "campus"         
## [29] "class"           "comfortable"     "girlfriend"      "home"           
## [33] "kitchen"         "problem"         "student"        
## 
## $x$freq
##  [1]  2  2  2  2  3  4  2  2  3  2  2  6  5  4  3 28  2 13  3  3  2  2  3  6  7
## [26]  3  5  5  2  7  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 6.428571
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.10.2 Don’t Belong

## $x
## $x$word
##  [1] "bad experience" "rich people"    "experience"     "kid"           
##  [5] "roommate"       "community"      "room"           "rude"          
##  [9] "student"        "people"         "friend"         "arc"           
## [13] "building"       "else"           "freshman"       "full"          
## [17] "hard"           "home"           "resident"      
## 
## $x$freq
##  [1]  2  2  2  4  3  2  2  2  4 19  8  2  2  2  3  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9.473684
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.11 Unthank

6.2.1.22.11.1 Belong

## $x
## $x$word
##  [1] "dining hall"    "other resident" "study room"     "good place"    
##  [5] "best friend"    "student"        "study"          "day"           
##  [9] "floor"          "room"           "people"         "group"         
## [13] "home"           "safe"           "friend"         "dinner"        
## [17] "time"           "comfortable"    "able"           "aspect"        
## [21] "building"       "class"          "coworker"       "end"           
## [25] "food"           "fun"            "girl"           "job"           
## [29] "nice"           "part"           "roommate"      
## 
## $x$freq
##  [1]  2  2  3  2  2  2  2  2  5  2 10  2  2  2 24  4  8  6  2  2  2  2  2  2  6
## [26]  3  2  2  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 7.5
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.11.2 Don’t Belong

## $x
## $x$word
##  [1] "dining hall"   "dining worker" "many people"   "floor"        
##  [5] "old"           "roommate"      "friend"        "group"        
##  [9] "people"        "building"      "food"          "freshman"     
## [13] "busy"          "campus"        "crazy"         "diversity"    
## [17] "don"           "else"          "hard"          "judgmental"   
## [21] "nervous"       "trouble"       "wealthy"       "weird"        
## 
## $x$freq
##  [1]  5  2  2  2  2  2  5  3 14  6  4  9  2  2  2  2  2  2  2  2  2  2  2  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 12.85714
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.12 Walton

6.2.1.22.12.1 Belong

## $x
## $x$word
##  [1] "good memory"    "freshman year"  "many friend"    "closest friend"
##  [5] "good friend"    "experience"     "floor"          "nice"          
##  [9] "friend"         "building"       "community"      "space"         
## [13] "wing"           "people"         "amazing"        "campus"        
## [17] "comfortable"    "fun"            "home"           "live"          
## [21] "ra"             "roommate"      
## 
## $x$freq
##  [1]  2  4  2  2  2  2  2  4 16  2  4  2  2 15  2  2  2  2  3  2  7  4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 11.25
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.1.22.12.2 Don’t Belong

## $x
## $x$word
##  [1] "freshman" "girl"     "student"  "building" "friend"   "chance"  
##  [7] "college"  "hard"     "home"     "night"    "people"   "roommate"
## [13] "uo"      
## 
## $x$freq
##  [1] 3 2 2 2 4 2 2 2 2 3 8 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 22.5
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.2 International

6.2.2.1 Erb Memorial Union

6.2.2.1.1 Overall Belong

## $x
## $x$word
##  [1] "international community" "courtyard dining"       
##  [3] "international student"   "other people"           
##  [5] "own homework"            "student"                
##  [7] "friendly staff"          "area"                   
##  [9] "group"                   "staff"                  
## [11] "space"                   "welcoming"              
## [13] "people"                  "event"                  
## [15] "class"                   "food"                   
## [17] "friendly"                "lunch"                  
## [19] "mill"                    "study"                  
## [21] "time"                    "day"                    
## [23] "friend"                  "break"                  
## [25] "campus"                  "comfortable"            
## [27] "desk"                    "fun"                    
## [29] "helpful"                 "music"                  
## [31] "nice"                    "person"                 
## [33] "relax"                   "welcome"                
## 
## $x$freq
##  [1]  2  2  7  2  3  2  2  2  2  2  2  2  9  4  2  2  4  2  5  2  2  3 19  2  2
## [26]  2  2  2  3  2  7  2  2  2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 9.473684
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 72 (n_Invalid = 2 removed). Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 24 students provided responses regarding one place, n = 15 provided responses regarding two places, and n = 6 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.2.1.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.2.1.3 Mills Center

6.2.2.1.3.1 Belong

## $x
## $x$word
##  [1] "international community" "international student"  
##  [3] "people"                  "welcoming"              
##  [5] "friend"                  "comfortable"            
##  [7] "event"                   "helpful"                
##  [9] "music"                   "nice"                   
## [11] "person"                  "study"                  
## [13] "welcome"                
## 
## $x$freq
##  [1] 2 7 2 2 6 2 4 2 2 4 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 25.71429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.2.1.3.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.2.2 Library

6.2.2.2.1 Belong

## $x
## $x$word
##  [1] "study room"  "quiet place" "good place"  "good"        "helpful"    
##  [6] "people"      "time"        "exam"        "peace"       "sense"      
## [11] "work"       
## 
## $x$freq
##  [1] 2 2 2 2 2 2 2 2 2 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 90
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.2.2.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.2.3 Lokey Science Complex

6.2.2.3.1 Overall Belong

## $x
## $x$word
## [1] "science" "class"   "nice"    "care"    "people"  "quiet"   "time"   
## 
## $x$freq
## [1] 2 3 2 2 4 2 4
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 45
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 22 (n_Invalid = 1 removed). Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 14 students provided responses regarding one place and n = 4 provided responses regarding two places. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.2.3.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.2.4 Student Rec Complex

6.2.2.4.1 Belong

## $x
## $x$word
##  [1] "great place" "fun"         "friendly"    "exercise"    "friend"     
##  [6] "campus"      "helpful"     "life"        "part"        "staff"      
## [11] "time"        "week"       
## 
## $x$freq
##  [1] 3 2 3 5 7 2 2 2 3 5 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 25.71429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.2.4.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.2.5 University Housing

6.2.2.5.1 Overall Belong

## $x
## $x$word
##  [1] "friendly" "people"   "food"     "dorm"     "friend"   "building"
##  [7] "day"      "dinner"   "home"     "nice"    
## 
## $x$freq
##  [1] 2 3 5 4 7 2 2 2 2 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 25.71429
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

Note: Word size represents frequency of keyword occurrence. Hover over words to see frequencies. The criterion for inclusion of a keyword in the wordcloud was occurrence \(\gt\) 1. If a word seems positively valenced, it was very likely negated (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 40. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 27 students provided responses regarding one place, n = 2 provided responses regarding two places, and n = 3 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text data were annotated using the udpipe package. Wordcloud was generated using the wordcloud2 package. Colors were produced using the rocket palette of the viridis package.

6.2.2.5.2 Overall Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.3 Graduate

6.2.3.1 Library

6.2.3.1.1 Belong

## $x
## $x$word
## [1] "quiet space" "people"      "quiet"       "safe"        "space"      
## [6] "student"     "interaction"
## 
## $x$freq
## [1] 2 3 2 2 3 3 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 60
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.3.1.2 Don’t Belong

Note: There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20.

6.2.3.2 Student Rec Complex

6.2.3.2.1 Belong

## $x
## $x$word
## [1] "people"   "body"     "exercise" "friendly" "gym"      "staff"   
## 
## $x$freq
## [1] 2 2 2 2 2 3
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#F6AA82"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 60
## 
## $x$backgroundColor
## [1] "#CB1B4F"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.2.3.2.2 Don’t Belong

## $x
## $x$word
##  [1] "most people" "gym"         "student"     "people"      "space"      
##  [6] "access"      "campus"      "hard"        "pool"        "staff"      
## 
## $x$freq
##  [1] 2 2 3 3 3 2 2 3 2 2
## 
## $x$fontFamily
## [1] "Segoe UI"
## 
## $x$fontWeight
## [1] "bold"
## 
## $x$color
## [1] "#78D6AE"
## 
## $x$minSize
## [1] 9
## 
## $x$weightFactor
## [1] 60
## 
## $x$backgroundColor
## [1] "#357BA2"
## 
## $x$gridSize
## [1] 0
## 
## $x$minRotation
## [1] 0.7853982
## 
## $x$maxRotation
## [1] -0.5235988
## 
## $x$shuffle
## [1] TRUE
## 
## $x$rotateRatio
## [1] 0.5
## 
## $x$shape
## [1] "circle"
## 
## $x$ellipticity
## [1] 0.65
## 
## $x$figBase64
## NULL
## 
## $x$hover
## NULL
## 
## 
## $width
## NULL
## 
## $height
## NULL
## 
## $sizingPolicy
## $sizingPolicy$defaultWidth
## NULL
## 
## $sizingPolicy$defaultHeight
## NULL
## 
## $sizingPolicy$padding
## NULL
## 
## $sizingPolicy$fill
## NULL
## 
## $sizingPolicy$viewer
## $sizingPolicy$viewer$defaultWidth
## NULL
## 
## $sizingPolicy$viewer$defaultHeight
## NULL
## 
## $sizingPolicy$viewer$padding
## [1] 0
## 
## $sizingPolicy$viewer$fill
## [1] TRUE
## 
## $sizingPolicy$viewer$suppress
## [1] FALSE
## 
## $sizingPolicy$viewer$paneHeight
## NULL
## 
## 
## $sizingPolicy$browser
## $sizingPolicy$browser$defaultWidth
## NULL
## 
## $sizingPolicy$browser$defaultHeight
## NULL
## 
## $sizingPolicy$browser$padding
## [1] 0
## 
## $sizingPolicy$browser$fill
## [1] TRUE
## 
## $sizingPolicy$browser$external
## [1] FALSE
## 
## 
## $sizingPolicy$knitr
## $sizingPolicy$knitr$defaultWidth
## NULL
## 
## $sizingPolicy$knitr$defaultHeight
## NULL
## 
## $sizingPolicy$knitr$figure
## [1] TRUE
## 
## 
## 
## $dependencies
## NULL
## 
## $elementId
## NULL
## 
## $preRenderHook
## NULL
## 
## $jsHooks
## $jsHooks$render
## $jsHooks$render[[1]]
## $jsHooks$render[[1]]$code
## [1] "function(el,x){\n                        console.log(123);\n                        if(!iii){\n                          window.location.reload();\n                          iii = False;\n\n                        }\n  }"
## 
## $jsHooks$render[[1]]$data
## NULL
## 
## 
## 
## 
## attr(,"class")
## [1] "wordcloud2" "htmlwidget"
## attr(,"package")
## [1] "wordcloud2"

6.3 Emotions

6.3.1 US Undergraduate

6.3.1.1 Allen

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 63. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.2 Autzen Stadium

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 117 (n_Invalid = 1removed). Total number of text responses used in analysis of “don’t belong” data was n = 63 (n_Invalid = 4removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.3 Cemetery

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 20 (n_Invalid = 1removed). Total number of text responses used in analysis of “don’t belong” data was n = 28. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.4 Chapman

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 33. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.5 Erb Memorial Union

6.3.1.5.1 Overall

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in this analysis was n = 977 (n_Invalid = 2 removed). Total number of text responses used in this analysis was n = 97 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2020 and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.5.2 Atrium East

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.3 Courtyard

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.4 Craft Center

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.5 Duck Nest

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.6 Falling Sky

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.7 Fishbowl

6.3.1.5.8 Fresh Market

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.9 LGBTQA3

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.10 Mills Center

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.11 Multicultral Center

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.12 O Lounge

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.13 Taylor Lounge

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.5.14 Women’s Center

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.6 Frohnmayer

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 52. Total number of text responses used in analysis of “don’t belong” data was n = 21 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.7 Hayward Field

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20. Total number of text responses used in analysis of “don’t belong” data was n = 148 (n_Invalid = 3 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the mako palette of the viridis package.

6.3.1.8 HEDCO

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 31 (n_Invalid = 1removed). Total number of text responses used in analysis of “don’t belong” data was n = 22 (n_Invalid = removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.9 Jaqua

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20. Total number of text responses used in analysis of “don’t belong” data was n = 74 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the mako palette of the viridis package.

6.3.1.10 Knight Law

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). There were no (or insufficient) “belong” text responses for this place. The threshold for minimum number of responses was 20. Total number of text responses used in analysis of “don’t belong” data was n = 57 (n_Invalid = removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the mako palette of the viridis package.

6.3.1.11 Lawrence

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 86. Total number of text responses used in analysis of “don’t belong” data was n = 22 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.12 Library

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 663 (n_Invalid = 1 removed). Total number of text responses used in analysis of “don’t belong” data was n = 207. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.13 Lillis Business Complex

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 197 (n_Invalid = 2 removed). Total number of text responses used in analysis of “don’t belong” data was n = 263 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.14 Lokey Science Complex

6.3.1.14.1 Overall

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 299 (n_Invalid = removed). Total number of text responses used in analysis of “don’t belong” data was n = 175 (n_Invalid = 7 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 207 students provided responses regarding one place, n = 35 provided responses regarding two places, n = 6 provided responses regarding three places, and n = 1 provided responses regarding four places within the Lokey Complex. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.14.2 Columbia

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.14.3 Klamath

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 34 (n_Invalid = 1 removed). Total number of text responses used in analysis of “don’t belong” data was n = 33 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket and mako palettes of the viridis package.

6.3.1.14.4 Lewis

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 23 (n_Invalid = 2 removed). Total number of text responses used in analysis of “don’t belong” data was n = 28. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket and mako palettes of the viridis package.

6.3.1.14.5 Science Commons

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.14.6 Willamette

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 64 . Total number of text responses used in analysis of “don’t belong” data was n = 52(n_Invalid = removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up the Lokey Science Complex as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (368, 94.8%), relatively few students contributed to two waves (20, 5.2%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket and mako palettes of the viridis package.

6.3.1.15 Matthew Knight Arena

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 47. Total number of text responses used in analysis of “don’t belong” data was n = 66 (n_Invalid = 4 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.16 McKenzie

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 29 (n_Invalid = 1 removed). There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.17 Oregon

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 33. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.18 Straub

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 56. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.19 Student Rec Complex

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 692 (n_Invalid = 2 removed). Total number of text responses used in analysis of “don’t belong” data was n = 575 (n_Invalid = 11 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.20 Tykeson

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 73 (n_Invalid = 1 removed). There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.21 University Health Services

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 27. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that were not subsequently aggregated into superordinate places and then disaggregated by subordinate places (i.e., not Erb Memorial Union, Lokey Science Complex, or University Housing) as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,820, 94.6%), relatively few students contributed to two waves (104, 5.4%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.1.22 University Housing

6.3.1.22.1 Overall

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 933 (n_Invalid = 7 removed). Total number of text responses used in analysis of don’t “belong” data was n = 487 (n_Invalid = 10 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. Additionally, students provided multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 619 students provided responses regarding one place, n = 136 provided responses regarding two places, and n = 14 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.2 Barnhart

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.22.3 Bean

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 136 (n_Invalid = 1 removed). Total number of text responses used in analysis of “don’t belong” data was n = 57. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.4 Carson

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 85 (n_Invalid = 1 removed). Total number of text responses used in analysis of “don’t belong” data was n = 34 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.5 Earl

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.1.22.6 Global Scholars

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 151. Total number of text responses used in analysis of “don’t belong” data was n = 93 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.7 Hamilton

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 175 (n_Invalid = 1 removed). Total number of text responses used in analysis of “don’t belong” data was n = 64. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.8 Kalapuya Ilihi

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 90. Total number of text responses used in analysis of “don’t belong” data was n = 58 (n_Invalid = 2 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.9 Living Learning

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 75 (n_Invalid = 0 removed). Total number of text responses used in analysis of “don’t belong” data was n = 49. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.10 Unthank

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 70. Total number of text responses used in analysis of “don’t belong” data was n = 52 (n_Invalid = 1 removed). Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.1.22.11 Walton

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Inflated prevalence of positive emotions in “don’t belong” results are very likely due to negation (e.g., preceded by the word “not”). Total number of text responses used in analysis of “belong” data was n = 54. Total number of text responses used in analysis of “don’t belong” data was n = 32. Generally, US undergraduates of all years/cohorts (mostly 1st-through-4th-year and predominantly first-year) contributed data in Spring 2019, Spring 2020, and Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once. Across all places that make up University Housing as well as across sentiments (i.e., “belong” and “don’t belong”), most students contributed to only one wave of data collection (1,016, 98.5%), relatively few students contributed to two waves (15, 1.5%), and no one contributed to three waves. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plots were generated using the ggplot2 package. Colors were produced using the rocket (Belong) and mako (Don’t Belong) palettes of the viridis package.

6.3.2 International

6.3.2.1 Erb Memorial Union

6.3.2.1.1 Overall

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 72 (n_Invalid = 2 removed). There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Erb Memorial Union to form an overall representation of the Erb Memorial Union as a unified place: n = 24 students provided responses regarding one place, n = 15 provided responses regarding two places, and n = 6 provided responses regarding three places within the Erb Memorial Union. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.2.1.2 Mills Center

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.2.2 Library

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.2.3 Lokey Science Complex

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 22 (n_Invalid = 1 removed). There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students could have contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up the Lokey Science Complex to form an overall representation of the Lokey Complex as a unified place: n = 14 students provided responses regarding one place and n = 4 provided responses regarding two places. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.2.4 Student Rec Complex

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

6.3.2.5 University Housing

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"

Note: Emotions are presented in rank order from most to least prevalent. Percentage = the percentage of all eligible words classified as being representative of one of eight emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust), based on Plutchik’s psychoevolutionary theory of emotion (Figure 1). Total number of text responses used in analysis of “belong” data was n = 40. There were no (or insufficient) “don’t belong” text responses for this place. The threshold for minimum number of responses was 20. Generally, degree-seeking international undergraduates (Freshman-through-Senior and predominantly Senior) contributed data in Spring 2020 and degree-seeking (first-year and second-year) and exchange international undergraduates and degree-seeking international graduates contributed data in Spring 2022. Because analyses combine data from multiple academic years, some students contributed data more than once, but none did. However, students did provide multiple responses for this particular analysis, because it combines responses regarding places that make up University Housing to form an overall representation of University Housing as a unified place: n = 27 students provided responses regarding one place, n = 2 provided responses regarding two places, and n = 3 provided responses regarding three places within University Housing. See Supplemental Method for more details. Text was annotated using the tidytext package. The nrc lexicon (Mohammad & Turney, 2013){target=“_blank”} was used to used to classify emotional content. Bar plot was generated using the ggplot2 package. Colors were produced using the rocket palette of the viridis package.

6.3.3 Graduate

6.3.3.1 Library

## <pointer: 0x0>
## attr(,"class")
## [1] "magick-image"