Welcome!
I’m Hauke, a post-doctoral researcher at the Cologne Center for Comparative Politics of the University of Cologne in Germany.
I develop and apply computational methods for the comparative study of political rhetoric. For example, in my dissertation I have examined how political text collections’ increasing volume, variety, and granularity can be harnessed to study party competition across countries and languages. And in an ongoing project together with Ronja Sczepanski (ETH Zurich), we develop a novel, deep learning-based method for extracting mentions of social groups from political texts that has been awarded the PolMeth Europe Best Poster Award for Innovative Data Science in 2022.
Substantively, I’m particularly interested in the role that rhetorical strategies play in democratic representation, electoral competition, and legislative politics. For example, in one of my dissertations papers, me and my co-authors apply machine learning methods to Twitter data to investigate how challenger and mainstream parties adapt their anti-elite rhetoric to coalition formation incentives and their standing in the polls.
Another part of my research focuses on multilingual text analysis and seeks to equip scholars and data analysts with novel tools to compare political processes and decisions across contexts and languages. For example, in my paper “Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings” published in Political Analysis, I show how translation-free, state-of-the-art transfer learning strategies can enable reliable cross-lingual political text analysis. And in a working paper co-authored with Fabienne Lind (University of Vienna), we provide a guide to multilingual text analysis for political and communication scientists.
Read more about my research and my professional activities in my CV. And feel free to email me or contact me on Twitter!