I am an Associate Professor in the Department of Sociology at the University of Copenhagen (UCPH) researching intergroup relations–such as between immigrants and natives, religious minorities and majorities, and political partisans–with a focus on the role of (mis)perceptions in conflict and cooperation. My work uses computational and experimental methods combining digital trace, text, survey, and administrative data. At UCPH, I am a co-organizer of the Experimental Methods in Sociology research group, a Fellow of the Copenhagen Center for Social Data Science (SODAS), and have served as the Director of Graduate Studies (studieleder) for the interdisciplinary MSc in Social Data Science from 2021 to 2023. Before joining the UCPH faculty, I earned a B.A.from Freie Universität in my hometown Berlin, Germany, and an M.A. and a Ph.D. from Duke University, in Durham, North Carolina.
My work combines different methods and data sources, including survey experimental methods to investigate how (mis)perceptions shape attitudes about immigrants and immigration, Google search data to study the link between discrimination and radicalization, original surveys to map what Americans think is the ideal racial-ethnic and religious makeup of their country, and contributions to large-scale replications examining the connection between immigration and welfare state support.
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.
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 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.