Week 13 Novel Approaches and Analytics

As we are coming to the final two weeks of this course, I hope we are all coming to appreciate the power of SNA and the relational perspective in general. It is totally fine if you are ‘still’ wrestling with certain areas of SNA, as every one of us brings unique perspectives into this course and may either need extra time to grasp certain concepts/techniques or wish to engage more deeply with certain areas. As the instructor, I will be most happy if this course would serve as a starting point for your journey with SNA.

SNA, and network analysis/science in general, are constantly evolving. The potential to apply SNA is endless. This week, we will explore some “unusual” use of SNA and, in some cases, a combination of SNA with other techniques.

13.1 Resources and Activities

In this week, each of us will:

  1. Identify/select a novel SNA-based approach, technique, or tool
  2. Review and critique the chosen approach or tool for our class

13.1.1 Resources

You have absolute freedom in choosing a novel SNA-based approach, technique, or tool. Below I provide a list of ‘candidates’ based on my areas of interest, which may not overlap with yours.

When making your choice, you should have a vague idea about what ‘novelty’ means to you. There is no standards to judge novelty in this course but it would be helpful if you can somehow justify your choice.

Research articles:

  • Shaffer, D. W., Collier, W., & Ruis, A. R. (2016). A Tutorial on Epistemic Network Analysis: Analyzing the Structure of Connections in Cognitive, Social, and Interaction Data. Journal of Learning Analytics, 3(3), 9–45. https://doi.org/10.18608/jla.2016.33.3
  • Vrana, V., Kydros, D., Kehris, E., Theocharidis, A.-I., & Karavasilis, G. (2019). A Network Analysis of Museums on Instagram. In A. Kavoura, E. Kefallonitis, & A. Giovanis (Eds.), Strategic Innovative Marketing and Tourism (pp. 1–10). Springer International Publishing. https://doi.org/10.1007/978-3-030-12453-3_1
  • Carley, K. M., Pfeffer, J., Morstatter, F., & Liu, H. (2014). Embassies burning: toward a near-real-time assessment of social media using geo-temporal dynamic network analytics. Social Network Analysis and Mining, 4(1), 195. https://doi.org/10.1007/s13278-014-0195-3 (Note: A collection of tools that extract network data from fairly free-form social media data.)
  • Stella, M., Beckage, N. M., & Brede, M. (2017). Multiplex lexical networks reveal patterns in early word acquisition in children. Scientific Reports, 7, 46730. https://doi.org/10.1038/srep46730
  • Ryu, S., & Lombardi, D. (2015). Coding Classroom Interactions for Collective and Individual Engagement. Educational Psychologist, 50(1), 70–83. http://doi.org/10.1080/00461520.2014.1001891 (Note: An attempt to combine SNA with critical discourse analysis.)
  • Oshima, J., Oshima, R., & Matsuzawa, Y. (2012). Knowledge Building Discourse Explorer: A social network analysis application for knowledge building discourse. Educational Technology Research and Development, 60(5), 903–921. http://doi.org/10.1007/s11423-012-9265-2 (Note: A novel tool developed for the analysis of discourse data, esp. by combining social and semantic aspects together.)
  • Andrade, A. (2015). Using Situated-Action Networks to visualize complex learning. In O. Lindwall, P. Hakkinen, T. Koschmann, P. Tchounikine, & S. Ludvigsen (Eds.), Exploring the Material Conditions of Learning: The Computer Supported Collaborative Learning (CSCL) Conference 2015, Volume 1 (pp. 372–379). Gothenburg, Sweden: International Society of the Learning Sciences. (Note: A theory-driven approach to develop a new network-based analytical approach.)
  • Vu, D., Pattison, P., & Robins, G. (2015). Relational event models for social learning in MOOCs. Social Networks, 43(Supplement C), 121–135. https://doi.org/10.1016/j.socnet.2015.05.001
  • Brandenberger, L. (2018). Trading favors—Examining the temporal dynamics of reciprocity in congressional collaborations using relational event models. Social Networks, 54, 238–253. https://doi.org/10.1016/j.socnet.2018.02.001
  • Quintane, E., Conaldi, G., Tonellato, M., & Lomi, A. (2014). Modeling relational events: A case study on an open source software project. Organizational Research Methods, 17(1), 23–50. https://doi.org/10.1177/1094428113517007


13.1.2 Reflect and Share

After spending time with resources related to the identified SNA-based innovation, you are expected to reflect on a few aspects:

  1. Which traditional SNA techniques are reflected in this innovation?
  2. Which ‘cool’ or ‘novel’ elements are introduced by this innovation compared to traditional SNA?
  3. Which practical and/or scholarly value does this innovation introduce?

Post your reflection on the Slack assignment channel. To warm up for our final project presentation, you can choose to make a mini video presentation (3-5 minutes) as well.

Have fun and I look forward to learning from your explorations!