Daniel Matter

PhD Candidate @ Technical University of Munich

I am a PhD candidate at the Chair for Computational Social Science at the Technical University of Munich. I am interested in the application of machine learning techniques to the field of computational social science, with a focus on the analysis of large-scale data sets. My research interests include the analysis of complex networks, the analysis of large language models, and the analysis of democracy in the age of digitalization.

About this Background

Research

I am a PhD candidate at the Chair for Computational Social Science at the Technical University of Munich, where I am lucky enough to be supervised by Jürgen Pfeffer. I am interested in the application of machine learning techniques to the field of computational social science, with a focus on the analysis of large-scale data sets. My research interests include the analysis of complex networks, the analysis of large language models, and the analysis of democracy in the age of digitalization.

Before my PhD, I have studied Mathematics, Computer Science, and Philosophy at the Technical University of Munich, National University of Singapore, and the Ludwig Maximilian University of Munich.

Projects

Russian Online Propaganda. Together with the research group Platform Algorithms and Digital Propaganda at Weizenbaum Institut, we investigate the spread and impact of Russian propaganda on social media platforms.
We recently released a preprint of our first paper, Temporally Stable Multilayer Network Embeddings: A Longitudinal Study of Russian Propaganda.

Online Firestorms. Together with the Chair of Applied Numerical Analysis, we are modeling the spread of online firestorms on social media platforms. Find out more at our project page.

Democracy in the Digital Age. tba.

Publications

Liu, Y., Matter, D., Pfeffer, J. (2025, April). Ideological Neural Manifolds of Large Language Models. Accepted at IC2S2.

Jiao, D., Liu, Y., Tang, Z., Matter, D., Pfeffer, J., Anderson, A. (2024, May). SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification. In ACL Findings.
DOI

Matter, D., Schirmer, M., Pfeffer, J. (2024, May). Investigating the Increase of Violent Speech in Incel Communities with Human-Guided GPT-4 Prompt Iteration. In Frontiers in Social Psychology.
DOI

Matter, D., Kuznetsova, E., Vziatysheva, V., Vitulano, I., Pfeffer, J. (2023, June). Temporally Stable Multilayer Network Embeddings: A Longitudinal Study of Russian Propaganda. In SNAMS 2023, Abu Dhabi.
ArXiv, IEEExplore

Pfeffer, J., Matter, D., Sargsyan, A. (2023, June). The Half-Life of a Tweet. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 17, pp. 1163-1167).
ArXiv, ICWSM

Pfeffer, J., Matter, D., Jaidka, K., Varol, O., Mashhadi, A., Lasser, J., Assenmacher, D., Wu, S., Yang, D., Brantner, C., Romero, D. M., Otterbacher, J., Schwemmer, C., Joseph, K., Garcia, D., Morstatter, F. (2023, June). Just Another Day on Twitter: A Complete 24 Hours of Twitter Data. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 17, pp. 1073-1081).
ArXiv, ICWSM

Contact Me