Daniel Matter

PhD Candidate at the Professorship of Computational Social Science and Big Data, Technical University of Munich

Daniel Matter is a PhD candidate at the professorship of Computational Social Science and Big Data. He has a background in Mathematics, Computer Science and Philosophy. His main areas of interest are social networks, opinion dynamics, and the effects of digitalization on democracy and and public discourse with a focus on natural language capabilities of artificial intelligence.

daniel.matter@tum.de
Profile
Participations and Contributions
Publications
Participations and Contributions
All posts
Digital politics

Development of AI-supported conversation training to foster democratic exchange (DemocraGPT)

Project

The research project DemocraGPT examines how large language models can support people in challenging political conversations, reduce reactance, and strengthen democratic conversational culture.

Publications

  • Matter, Daniel; Schirmer, Miriam; Grinberg, Nir; Pfeffer Jürgen (2024)

    Investigating the increase of violent speech in Incel communities with human-guided GPT-4 prompt iteration

    Journal article
    Frontiers in Social Psychology, Volume: 2
    DOI: 10.3389/frsps.2024.1383152
    Project: Misogyny_2.0