Hi! I’m a Research Fellow at the Institute for Advanced Study in Toulouse, University of Toulouse 1 Capitole, in France (IAST).

I did my PhD in Sociology at the University of Groningen (UG) and the Interuniversity Institute for Social Science Theory and Methodology (ICS). In the Norms and Networks Cluster I studied micro-macro processes of opinion formation. Afterwards, I was a Postdoctoral researcher at the Chair of Sociology and Computational Social Science in the Karslruhe Institute of Technology (KIT).

My main interest lies in computational social science and complexity science. Specifically, theoretical and empirical modeling of online behavior and digital trace data. In my PhD research I focus on the impact of communicating via online social media platforms on processes of opinion formation and the diffusion of culture. Please read more about my research interest here.

News and Updates

April 2021 \\ I’m joining the Chair of Sociology II at the Institute of Technology Futures, Karlsruhe Institute of Technology (ITZ-KIT) as a Postdoctoral Researcher this month. Here, I look forward to continuing my work on (empirical validation of) models for opinion dynamics on the internet together with Professor Michael Mäs.

logo February 2021 \\ Next month, on March 15 at SocSimFest 2021 (held online), Dieko Bakker, Anton Laukemper and I will be organizing a workshop entitled ‘Social Influence Modeling in Python Using defSim’. In this tutorial, the participants receive a thorough introduction into the software, and hands-on experience with modeling of social influence processes. Upon completion, participants will be able to use defSim in their own research or teaching. If you’re interested in participating in the workshop, visit the website of SocSimFest for more information.

December 2020 \\ How can social bots influence public debate in online social media? The next issue of Online Social Networks and Media will feature my paper The Strength of Weak Bots. In this paper, Michael Mäs and I investigate how social bots–spreaders of misinformation and falsehoods in online social media–can most effectively persuade populations of individuals using insights from the opinion dynamics literature. We show that, surprisingly, bots that are less well connected and not too active can be much more effective than you might think. This finding resonates with empirical findings on the effectiveness of social bots, as the microblogsphere of social bots seems to stand largely disconnected from the human spheres, yet appears to be effective at propagating falsehoods regularly.
[paper] [code]

logo October 2019 \\ I’ve been working on a python package for agent-based modeling with Anton Laukemper. Our discrete event framework for social influence models, or defSim, is now live! The open-source package is freely available on GitHub, and contributions to the code are welcomed. In the coming months we will release tutorials on how to use defSim, and information on how to contribute, so stay tuned.

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Website was last updated on October 21, 2021