How does a news story go viral? Which politicians communicate most effectively through Instagram? How does Google try to avoid showing conspiracy theories at the top of its search results? To address and answer such questions, this course blends insights and practical techniques from the emerging fields of computational social science, digital analytics, and critically-oriented, so-called digital methods. Specifically, the course proposes a two-sided approach: On the one hand, it equips students with practical computational skills to access, gather, process, and analyze web data and metrics, such as social media page and post data. Free analytics software tools, Microsoft Excel, and the R programming language will be used for those steps in hands-on, workshop-style lessons. On the other hand, the course introduces students to ideas and theoretical concepts that allow them to critically assess and make sense of the often messy and ephemeral nature of web data. This includes a critical understanding of the properties and working logics of key elements of the web, such as search engine and newsfeed algorithms, hyperlink networks, and social media metrics.
- Enseignant·e: Julian Maitra
- Enseignant·e non éditeur: Nadège Françoise Rives