Patrice Wangen

Patrice Wangen


Member of:

  • Copenhagen Center for Social Data Science (SODAS)

I am a postdoctoral researcher at the University of Copenhagen working on diplomatic practices in the era of social media and digital communication. I hold a Ph.D. in Political and Social Sciences from the European University Institute, a MSc in European Studies from Maastricht University, and a BA in Political Science and History from the University of Greifswald.

Diplomacy, Armed Conflicts, and Media Analysis

In the DIPLOFACE project, we aim to understand how practitioners of international relations (re-)negotiate the relationship between backstage negotiations and public display of politics; between classical journalism and new forms of digital communication; between face-to-face meetings and digital portrayals of political relationships.

I am also interested in the origins and dynamics of armed conflicts. In particular, my Ph.D. thesis aimed to understand Western attempts to intervene in conflicts around the world, and how media discourses about the latter influence Western perceptions of and policies towards war and violence abroad.

Critical Quantitative Methodology

Throughout my work, I am exploring how explicitly post-positivist discourse and sociological theories can be productively combined with advanced statistical and data science methods. In my Ph.D thesis, I explored how the discourse theory of Ernesto Laclau, Chantal Mouffe, and Slavoj Žižek can be applied – in a methodologically consistent way – to machine-learning-based text classification algorithms, as well as to quantitative approaches to the study of causality. In my current work in the DIPLOFACE project, I am furthermore exploring how these methods can be constructively used to complement insights from more qualitative and ethnographic approaches to the study of diplomatic practices.

I am an irredeemable methodological pluralist and convinced that quantitatively working political scientists can learn a lot from taking post-positivist theories more seriously. In turn, scholars building on the latter perspectives miss out on interesting insights if they a priori exclude statistical methods from their research agendas because the positivist biases of their most vocal defenders. I show in my work that statistical tools are methodologically much more flexible and can be creatively combined with a variety of different ontologies and epistemologies.

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