Computational Social Science of Social Media Misinformation

Thursday, 16. May 2024
11:45 - 13:00

Y213 & online

Cluster of Excellence "The Politics of Inequality"

Viola Priesemann and David García

Online social media are a major channel for political communication, bringing concerns about the role of social media platforms in the spreading of misinformation and polarizing content. We will discuss approaches from Computational Social Science and Complexity Science to model and analyze political phenomena in social media. We will have a special focus on novel methods to collect data from Telegram channels, on text analysis to identify populist rhetoric, and on observational analysis of content spreading as a function of news source trustworthiness. This workshop is part of a larger meeting between the labs of Viola Priesemann and David Garcia, seeking a conversation with the interdisciplinary audience of the cluster to identify research questions and uses for our datasets and methods. 

Viola Priesemann is a physicist and neuroscientist at the Max Planck Institute for Dynamics and Self-Organization and Professor of physics at the University of Göttingen. After research projects at the Ecole Normale Superieure Paris (France) and the Caltech (USA), she obtained her PhD at the MPI for Brain Research and the University of Frankfurt. As postdoc and Fellow at the Bernstein Center Göttingen she applied for an independent Max Planck Research Group, which started in 2017 at the MPI in Göttingen. Viola Priesemann studies self-organization and learning in living and artificial networks, illuminating the basic mechanisms that shape collective information processing.

David García is Professor for Social and Behavioural Data Science at the University of Konstanz since 2022 and currently Internal Senior Fellow at Cluster of Excellence “The Politics of Inequality”. David has expert knowledge in Computational Social Science investigating human behavior through digital traces with methods from complexity science. Analyzing big social data by using computational modeling, he aims to understand the impact of line media and social media networks on individuals and society (e.g. inequalities, data privacy).

Online Participation: 

Meeting ID: 880 5144 0770
Passcode: 746761