In my research, I aim to address substantive and policy-relevant political science questions using micro-level data and state of the art quantitative methodology. In the past years, the main focus of my research has been on understanding the influence of new digital online media for political behavior. Methodologically I am interested in statistical methods for the analysis of data gleamed from digital media and big data analytics but also computational (agent-based) modeling and the analysis of highly-resolved geographical data. I also work on developing methods for causal inference in event data.

The two main research projects that I am currently involved in are both highly interdisciplinary with researchers hailing from different substantive fields. The WIN project is a joint project with a colleague in computer science at the University of Wuppertal on the automated detection of media bias in news media articles. This project connects a long tradition of social science research on media bias with state-of-the-art deep learning approaches from computer science.

The StopHateSpeech project is led by alliance F (Federation of Swiss Women’s Associations) and implemented in close collaboration with the research institute sotomo, the IT-company ama-sys, the Digital Democracy Lab (UZH) and the Public Policy Group and Immigration Policy Lab (ETH). The project combines natural language processing and machine learning with civil society engagement to counter online hate speech.

You may find further details on ongoing and past research initiatives under Projects and please refer to Publications for for a list of my academic publications. Together with colleagues I have further developed a number of Software packages that are available under open source licenses. Information related to newspaper, radio and TV coverage of my research may be found under Media Coverage.