I enjoy analyzing all forms of political communication (e.g., social media, speeches, or press releases) with both, state-of-the-art machine learning models and traditional approaches to answer substantial research questions in Political Science. In the course of my Master thesis I developed a framework to estimate legislator-level salience and position estimates based on political text using Transformers. In Fall 2022 I will teach a postgraduate seminar at TU Darmstadt providing an introduction to quantitative methods in R for political scientists. My substantial interests focus on political communication and intra-party heterogeneity.

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