Two-weeks of intense computational social sciencing in the rearview mirror.
I am an Assistant Professor in the Department of Sociology at the University of Copenhagen and the Director of Graduate Studies (studieleder) for the interdisciplinary MSc in Social Data Science. At UCPH, I am also affiliated with the Copenhagen Center for Social Data Science (SODAS) and coordinate the Welfare, Inequality, and Mobility research group. In my research, I use computational and experimental methods to examine intergroup relations leveraging digital trace, text, survey, and administrative data. Before joining the UCPH faculty, I earned my B.A.from Freie Universität in my hometown Berlin, Germany, and my Ph.D. from Duke University, in Durham, North Carolina.
In my recent work, I have used Google search data to study the link between discrimination and radicalization; and combined digital trace data, large-scale field experiments, and panel surveys to test the effect of exposure to opposing views on social media on political polarization and the impact of the Russian influence campaign on US Twitter user political attitudes and behavior.
Ph.D. in Sociology, 2019
Duke University
M.A. in Sociology, 2017
Duke University
B.A. in North American Studies, 2014
Freie Universität Berlin, Germany
I am teaching or co-teaching a number of classes at the University of Copenhagen ranging from political sociology to introductory Python and R.
At the Department of Sociology, I (co-)instruct the following classes:
In the MSc in Social Data Science, I (co-)instruct the following classes:
I am also teaching occasional workshops on introductory R (e.g. at GESIS (October 2021, October 2022) or the Copenhagen Summer University) or the use of the texnets
R package, and have previously been part of the organizing team for the Summer Institutes in Computational Social Science.
Below, you can find more detailed descriptions and material for selected courses.
An introductory level course for learning quantitative text analysis methods and their implementation in R.
Two-weeks of intense computational social sciencing in the rearview mirror.
Two-week immersive summer school for social and data scientists interested in computational social science.
Learn how to combine quantitative text analysis with graph theory in Cologne in December.