• Maitra Julian

What news stories go viral on Instagram? Does the party-affiliation and gender of Swiss politicians affect their visibility and user interactions on Facebook? Which accounts and messages dominate the debates on climate change and migration on TikTok and X?

This course teaches you how to address and answer such questions through social media data analysis. The course pursues a two-sided approach:

- On the one hand, it equips students with practical computational skills to access, gather, process, and analyze social media data and metrics. To do this, the course introduces students to the R programming language and various open-source analytics tools (e.g. APIs) in hands-on, workshop-style lessons.

- On the other hand, the course aims to sharpen the critical thinking skills of students, namely their ability to critically assess, interpret, and debate in class some of the current developments, controversies, and ethically problematic issues in social media. Both quantitative and qualitative approaches will be used to achieve this.

The course also requires students to read and engage with some of the latest research on social media and its role in society.

- Be able to access, gather, process, and analyze social media data through computational techniques. Specifically, be able to apply the R programming language at a basic level, notably to manipulate, analyze, and visualize social media data, for example, in scatter plots, histograms, and word clouds.

- Be able to combine quantitative insights and critical reasoning to qualitatively make sense of social media data and their role in the public sphere.

- Be able to understand, present, and discuss the major findings of published research on social media (group presentation).

- Be able to create a written report of your own social media data analysis (individual written work).

Sloan, L., & Quan-Haase, A. (2022). The Sage handbook of social media research methods (2nd ed.). Sage.

Van Atteveldt, W., Trilling, D., & Calderon, C. A. (2022). Computational analysis of communication. John Wiley & Sons. https://cssbook.net

Wickham, H., Çetinkaya-Rundel, M., & Grolemund, G. (2023). R for data science (2nd ed.). O'Reilly. https://r4ds.hadley.nz 

Exam duration: 15 minutes

Retake exam only, not valid for a first try

The evaluation occurs in two steps:
- Group presentation (40% of the grade) in which you explain and discuss a published scholarly study about a social media phenomenon.
- Individual written work (60% of the grade): A short empirical paper that contains your own social media data analysis.

Course with continuous evaluation: after the registration period, you can no longer cancel your registration (see session calendar on the Faculty's website).