Recent Publications

Software

Coming soon..

Teaching

Since 2011 I teach seminars and workshops on both substantive subjects and research methods.

  • PhD Workshop, (12h) Causal Inference, European University Institute, Florence, 12/13/15.12.2016
  • PhD Seminar, (17h) Data Visualization (with Richard Traunmüller), CUSO Doctoral Programs, Bern, 4-5.11.2016
  • B.A. Workshop, (3h) Causal thinking and inference (PPE, 3rd year), UPF, Barcelona, 5.5.2016
  • Sessions (2 * 2h) on Game theory/strategic interaction and Norms within “Foundations of Social Life” (Prof. Gambetta), EUI, Florence, 23.2./3.1.2016
  • PhD/PostDoc Workshop (12h), R programming and data analysis, EUI, Florence, 3./4.3.2016
  • M.A./B.A. Seminar, Foundations of quantitative data analysis, Bern, Autumn term 2015
  • B.A. Workshop, Interactive and dynamic data visualization within “Datenvisualisierung für die Empirische Demokratieforschung” (Prof. Richard Traunmueller), Frankfurt, May 2015
  • PhD Workshop, Causal inference within “Citizens Behavior and Attitudes in Switzerland and Europe”, Doctoral Program in Political Science (CUSO), Murten, May 2015
  • M.A. Seminar, Dataanalysis with R (with Rudi Farys), Bern, Spring term 2015
  • Session on Measuring trust and trustworthiness within “Foundations of Social Life II: Trust and Trustworthiness” (Prof. Gambetta, EUI), Florence, January 2015
  • B.A. Seminar, Foundations of quantitative data analysis, Bern, Autumn term 2014
  • M.A. Seminar, Dataanalysis with R (with Rudi Farys), Bern, Spring term 2014
  • B.A. Seminar, Trust and trustworthiness, Bern, Spring term 2013
  • M.A. Seminar, Dataanalysis with R (with Rudi Farys), Bern, Spring term 2013
  • Teaching Assistant, Political Sociology, Prof. Markus Freitag, Bern, Autumn term 2012
  • B.A. Seminar, Comparative attitudinal and behavioral research, Bern, Spring term 2012
  • Teaching Assistant, Social Capital, Prof. Markus Freitag, Bern, Spring term 2011
  • Teaching Assistant, Political Sociology, Prof. Markus Freitag, Bern, Autumn term 2011
  • Compact course, Introduction to R, Konstanz, Winter term 2011
  • Teaching Assistant and Tutor, Comparative Politics, Prof. Markus Freitag, Konstanz, Summer term 2010

Visualization

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.

Transformations of variables/data: A simple app to illustrate what happens to the the distribution of a variable when it is transformed. 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.

WorkingPapers

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

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