How does a news story go viral on Instagram?

Do politicians' party affiliation and gender affect their visibility and user interactions on Facebook?

Which hashtags dominate the debate on climate change on Twitter?

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, notably from Instagram, Facebook, and Twitter.
    To do this, the course introduces students to the R programming language and various open-source analytics tools 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.

This also requires considering some of the latest research on those topics.

Grading occurs in two parts.

  • Part I: 40% take-home problem sets to be solved in R (individually, to be submitted throughout the semester).
  • Part II: 60% term paper on your own social media data analysis and critical discussion (individually, essay of 1500-2500 words, can be written in English, French, or German).
Training objectives

  • 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 and word clouds
  • Be able to combine technical insights and critical reasoning to make sense of social media data and the complex interplay between social actors and technical systems that led to the creation of those data
  • Improve your academic writing skills