Chapter 1 Introduction

Dear student,

if you read this script, you are either participating in one of my courses on digital methods for the social sciences, or at least interested in this topic. If you have any questions or remarks regarding this script, hit me up at .

This script will introduce you to three techniques I regard as elementary for any aspiring (computational) social scientist: first, the collection of digital trace data via either scraping the web or acquiring data from application programming interfaces (APIs); second, the simulation of human behavior using agent-based modeling; and, third, the analysis of text in an automated fashion (text mining).

The following chapters draw heavily on packages from the tidyverse (Wickham et al. 2019) and related packages. If you have not acquired sufficient familiarity yet, you can have a look at the excellent book R for Data Science by Hadley Wickham (2016) or the not so excellent introductory script I have written.

References

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the Tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.
Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. First edition. Sebastopol, CA: O’Reilly.