Theresa Henn

Theresa Henn is a research associate at the Chair of Information Systems and Social Networks at the University of Bamberg. From 2020 to 2023, she worked as a project associate on the project “How do the central social conflict structures change within Germany? Social media analytics of collective protests and movements” funded by the Bavarian Research Institute for Digital Transformation (bidt).

She studied political science with a focus on economics (B.A.) at the University of Mannheim and Trinity College Dublin. For her master’s degree in political science with a focus on computational social sciences (M.A.), she moved to the University of Bamberg and spent a semester abroad at Sciences Po Lille. In 2022, she participated in the three-month “Data Science for the Social Good” fellowship at the Rhineland-Palatinate Technical University of Kaiserslautern-Landau (RPTU) and the German Research Center for Artificial Intelligence (DFKI), organized in collaboration with Carnegie Mellon University and the University of Warwick.

Theresa’s research focuses on the analysis of online communities, particularly in the context of protest movements. She is especially interested in boundary dynamics of online collectives, shaped by processes such as the formation of collective identities, media coverage and the framing of protest movements online, as well as cultural diffusion processes on social media, for example, through memes. Methodologically, she focuses on image analysis, network analysis, and statistical methods. Her research has been published in academic journals like PLOS One and in conference proceedings such as ICIS and ECIS.

In 2022, Theresa was nominated for the “Teaching Award” of the Faculty of Information Systems and Applied Computer Sciences (WIAI) and received this award in 2023.

Research Interests

  • Online Communities, Protest Movements & Social Media
  • Machine Learning, especially Image Analysis
  • Social Network Analysis, espeically Socio-Semantic Analysis

Teaching

Theresa Henn supports:

  • "Wissens- und Informationsmanagement"  - Bachelor lecture
  • "Ausgew?hlte Themen der Wirtschaftsinformatik" - Bachelor course
  • “Analyse sozialer Netzwerke“ - Master lecture
  • "Netzwerktheorie" - Master lecture
  • "Project Online Social Networks" - Master course
  •  Supervision of final theses

Selected Publications

Henn T, Posegga O (2024) 
Peeking behind the Memes: Evaluating the Boundary Work of Online Communities through Shared Memes.
Proceedings of the International Conference on Information Systems (ICIS).
https://aisel.aisnet.org/icis2024/socmedia_digcollab/socmedia_digcollab/8/

Henn, Theresa (2024).
Follow the Memeing: Analyzing the Cultural Diffusion between Mainstream and Alt-Right Communities based on Shared Memes. 
Proceedings of the European Conference on Information Systems (ECIS). https://aisel.aisnet.org/ecis2024/track24_socialmedia/track24_socialmedia/11/

Henn T, Posegga O (2023) 
Attention-grabbing news coverage: Violent images of the Black Lives Matter movement and how they attract user attention on Reddit.
PLOS ONE 18(8): e0288962. 
https://doi.org/10.1371/journal.pone.0288962

Henn T, Posegga O (2023) 
What Do They Meme? Exploring the Role of Memes as Cultural Symbols of Online Communities.
Proceedings of the International Conference on Information Systems (ICIS). https://aisel.aisnet.org/icis2023/socmedia_digcollab/socmedia_digcollab/8/

Further Conference Participation

Deutsche Gesellschaft für Netzwerkforschung Kongress 2024:
Order from Chaos: Warum sich Harrison White zur Analyse von kollektiven Identit?ten im digitalen Raum eignet

International Conference for Computational Social Science (IC2S2) 2023: 
The Emergence of Collective Identities Online: Detecting Patterns in Social Movement Formation on Twitter

Deutsche Gesellschaft für Soziologie Kongress 2022:
Inwieweit lassen "digital trace data" Rückschlüsse auf die kollektive Identit?t sozialer Bewegungen zu?

Sunbelt - International Network for Social Network Analysis (INSNA) Conference 2022:
Conceptualizing and Measuring Collective Identity Online