Stefan Müller is a Postdoctoral Researcher at the Chair of Public Policy and affiliated with the Digital Democracy Lab. He will receive his PhD degree from the Department of Political Science at Trinity College Dublin. He is a core contributor to the quanteda R package, Documentation Manager and Training Advisor of the Quanteda Initiative, and author of extensive tutorials on quantitative text analysis. In his PhD thesis, he reassessed the concept of election pledges, analysed circumstances under which political parties decide to make promises, claim credit or attribute blame, and examined how the media report on election promises. His published work investigates support for government parties throughout the electoral cycle, party preferences under cumulative voting, and determinants of the (dis-)approval of personalised, but complex electoral systems. Currently, he is involved in collaborative projects on parties, coalitions, public opinion, the impact of challenger quality on the incumbency advantage, legislative behaviour, political compromise, and the efficient and reliable combination of machine learning and crowd-sourced text coding.
Representation, Party Competition, Policy Analysis, Voting Behaviour, Public Opinion, Computational Social Science