Event

The Internet has become an arena for public debate, providing users with unprecedented means of communicating their opinions and political views via online fora, tweets, Facebook posts, and the like. Many fear that this new technology changes public debate in ways that endanger societal cohesion and democracy, pointing to phenomena like filter bubbles or fake news. This seminar covers the computational social science approach to this research field, highlighting the opportunities and challenges that come with learning about human behavior in an increasingly data driven society. Specifically, we discuss theories and empirical research on opinion dynamics on the Internet, and focus on computational models of opinion dynamics in networks and their application to online (social media) platforms. We explore how social influence on the Internet can be studied empirically with experiments and the analysis of digital trace data, but stress the importance of theoretically well-informed models when doing so. In this course, students will have the opportunity to explore alternative methods from the emerging field of computational social science, analyzing computational models of opinion dynamics on the Internet, or gathering and analyzing data on the web. 

The course consists of two parts (5011018 and 5011002) that need to be taken in parallel. It is not possible to attend only one of the two courses. To enroll to both parts, please use the registration procedure of course 5011018.