Welcome! I am a Max Weber Fellow at the European University Institute. In April 2015 I finished my PhD at the Institute of Political Science at the University of Bern. Before I studied at the University of Konstanz, the University of Pompeu Fabra and at Sciences Po Bordeaux. During my studies I spent longer periods in Tunisia and Vietnam.
My areas of interest include political sociology - trust, attitudes, values and polarization - and research methods - measurement, causal inference and data visualization. I cofounded and co-organize a quantitative methods working group at the EUI.
On this website you will find information about my research and maybe occasionally a post about something that is somehow related to my research. You can find my papers under ‘research’ on this website and/or on SSRN/Research Gate.
Dr - Political Science, 2015
University of Bern
MA - Political and Social Sciences ('European Master in Government'), 2010
University of Pompeu Fabra, Barcelona
MA - Public Administration ('European Master in Government'), 2010
University of Konstanz, Germany
BA - Politics and Public Administration, 2008
University of Konstanz, Germany
Since 2011 I teach seminars and workshops on both substantive subjects and research methods.
Below some visualizations used both for teaching and research purposes. I mainly work with R, Shiny and Plotly and I am very interested in the potential of interactive data visualization. Most of my projects are published on my github repository. Please contact me if you have any feedback or questions.
Guessing distributions: I used this app in a course on the foundations of quantitative analysis. The idea is that students can use the app to become familiar with various distributions. In class participants can guess what distributions of certain variables should look like and discuss them subsequently. You can find the app here and the code on github.
Measurement error (Bull’s eye): This app serves to explain the concepts of systematic and random measurement error. Thereby, it relies on the example of a single person that repeatedly measures his/her weight on a scale. You can change the number of measurements (observations), i.e. how often the person measures his/her weight, as well as the random error and the systematic error underlying these repeated measurements. You can find the app here and the code on github.
Visualizing functions: This app allows for plotting different functions. You can choose a certain function, decide about the range for which the function should be plotted and the range of x- and y-values for which the plot is displayed. You can find the app here and the code on github.
Joint distributions (discrete variables): I used this app in a course on the foundations of quantitative analysis. Just as for the app visualizing univariate distributions the idea is that students become familiar with joint distributions and develop a “distributional perspective” on data. You can find the app here and the code on github.
Systematic measurement error in subgroups: This app gives a simple example of how distributions change as a consequence of systematic measurement error. It also illustrates how a variable’s distribution changes if there are different systematic measurement errors across subgroups that operate simultaneously. You can find the app here and the code on github.
Conceptualizing Trust and Trustworthiness. (Working paper published in the Political Concepts - Committee on Concepts and Methods Working Paper Series, No. 61.)
Political Trust in Switzerland: Again a special case? Book chapter prepared for “Identities, Trust, and Cohesion in Federal Countries: Perspectives from Public Opinion” edited by John Kincaid and Jack Jedwab, McGill-Queen’s University Press. (with Markus Freitag and Pascal Sciarini)
The quality of citations: Towards quantifying qualitative impact in social science research (with Pablo Barberá and Simon Munzert)
The Visual Display of Causal Relationships
Conceptualizing and Measuring Opinion Polarization