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Computational Social Scientist in Online Political Communication & Platform Governance

I am Daniel Cowen, a PhD candidate in Computational Social Science at the University of Groningen. My research focuses on online political communication, platform governance, and the dynamics of hostile discourse in digital spaces.

I study how hostility spreads and can be interrupted in threaded online political discussions, combining large-scale digital trace analysis, NLP, Bayesian modelling, and agent-based simulation. My work examines toxic cascades and bridging behaviours in online political communities, using Habermas’ theory of the public sphere to connect empirical findings to questions of democratic speech, platform design, and the boundary between harmful content and legitimate contestation. I work at the intersection of theoretical and computational social science, political communication, and platform studies.

Research Interests

  • Longitudinal intergroup dynamics and social identity formation
  • Online political communication and hostile discourse repercussions
  • Computational social science and digital trace analysis
  • Natural language processing for detecting toxicity and bridging behaviors
  • Habermasian public sphere theory in digital contexts
  • Agent-based modeling of social phenomena

Current Research

PhD in Computational Social Science — University of Groningen (November 2022 – December 2026 (expected))

Part of the SCOOP (Sustainable Cooperation Program) and the ICS (Interuniversity Center for Social Science Theory and Methodology). My research on identities, networks, and cooperation focuses on understanding how online platform design shapes discourse dynamics and cooperation potential in politically divided communities.

Technical Skills

  • Programming Languages: Python, R, NetLogo, JavaScript
  • NLP & Text Analysis: Sentiment analysis, toxicity detection, discourse analysis
  • Statistical Methods: Bayesian modeling, network analysis, causal inference, agent-based modelling
  • Tools & Libraries: scikit-learn, NLTK, spaCy, tidyverse, networkx, MESA, data visualization
  • Data Collection: Web scraping, API integration, digital trace analysis

Personal

Outside of academia, I enjoy playing tennis, making music, and (admittedly) reading about political systems in countries I am not from.