Research areas

• – Computational social science
• – Mathematical modeling
• – Social media
• – Linguistic networks

Methodological and/or psychotherapeutic expertise

• – Complexity
• – Markov chains
• – Dynamical systems
• – Network science

Short biography

Dr. Sven Banisch pursues research in Computational Social Science to understand social phenomena that involve processes of opinion formation. He uses computational models to explore how social and psychological processes involved in platform-mediated communication play out at the scale of large collectives in modern information society. Sven also participates in the development of social media observatories and computational tools for the socio-semantic mapping of online debates. He is currently working at the Institute of Technology Futures at KIT.

Relevant publications

• Banisch, S., & Olbrich, E. (2019). Opinion polarization by learning from social feedback. The Journal of Mathematical Sociology, 43(2), 76-103.
• Törnberg, P., Andersson, C., Lindgren, K., & Banisch, S. (2021). Modeling the emergence of affective polarization in the social media society. Plos One, 16(10), e0258259.
• Banisch, S., & Shamon, H. (2024). Validating Argument-Based Opinion Dynamics with Survey Experiments. Journal of Artificial Societies & Social Simulation, 27(1).
• Banisch, S., & Shamon, H. (2023). Biased Processing and Opinion Polarization: Experimental Refinement of Argument Communication Theory in the Context of the Energy Debate. Sociological Methods & Research, 00491241231186658.
• Westermann, S., & Banisch, S. (2024). A Formal Model of Affiliative Interpersonality. Clinical Psychological Science. doi:10.1177/21677026241229663
• Banisch, S., Gaisbauer, F., & Olbrich, E. (2022). Modelling spirals of silence and echo chambers by learning from the feedback of others. Entropy, 24(10), 1484.
• Olbrich, E., & Banisch, S. (2021). The rise of populism and the reconfiguration of the German political space. Frontiers in Big Data, 4, 731349.
• Jacob, D., & Banisch, S. (2023). Polarization in social media: A virtual worlds-based approach. Journal of Artificial Societies and Social Simulation, 26(3).
• Banisch, S. (2016). Markov chain aggregation for agent-based models. Springer.
• Banisch, S., Lima, R., & Araújo, T. (2012). Agent based models and opinion dynamics as Markov chains. Social Networks, 34(4), 549-561.
• Gaisbauer, F., Pournaki, A., Banisch, S., & Olbrich, E. (2021). Ideological differences in engagement in public debate on Twitter. Plos One, 16(3), e0249241.

Relevant funded research projects

• – SoMe4Dem (Social Media for Democracy), Horizon Europe, www.some4dem.eu infoXpand (Interactions between the infodemic and the pandemic), BMBF
• – Scientific Network Computational Clinical Psychology and Psychotherapy Network (ccpp.network): Formal models and empirically informed simulations of the formation, maintenance and change of psychopathology (DFG project; started in 2024)