Morgan Wack

I am a Postdoctoral Scholar in the University of Zurich's Department of Communication & Media Research (IKMZ). My research is focused on understanding how digital technologies are used to influence the public. This includes research into novel forms of disinformation and the use of LLMs to develop propaganda, as well as work developing interventions to mitigate their impact. My work draws on mixed and computational methods, including algorithmic auditing, machine learning–assisted classification, large-n text analysis, and survey and field experiments, with research projects spanning the United States, Europe, and sub-Saharan Africa.

Previously, I was a Research Assistant Professor at Clemson University's Media Forensics Hub. I received my PhD from the University of Washington. I am the consulting scientist for the International Panel on the Information Environment (IPIE)'s Indexing Panel, an affiliate of the Center for Information, Technology, and Public Life (CITAP), and a member of both the Coalition for Independent Technology Research (CITR) and DSI Digital Publics communities.

Recent Publications/Preprints


Pipal, C. and Wack, M. and Profos, A.A. and Vogel, E.-M. and Wittstock, N. and Mpadanes, M. (2026). When Does Self-Correction Work for LLMs in Content Analysis? The Role of External Structure and Task Complexity. Computational Communication Research, 8(2), 1--35. Read →
Jalbert, M. and Wack, M.. (2026). Intuitions about content moderation are misaligned with effective practices for reducing conspiracy beliefs. Communications Psychology. Read →
Pipal, C. and Vogel, E.-M. and Wack, M. and Esser, F. (2026). Researchers Waste 80% of LLM Annotation Costs by Classifying One Text at a Time. Under Review Read →
Wack, M. and Vogel, E.-M. and Pipal, C. and Warren, P. (2026). Fact-Checks Can Help Inoculate LLMs Against Disinformation. Under Review Read →
Blessing, J.N. and Wack, M. and Mahl, D. (2026). AI Can Correct but Not Convince: Epistemic Authority and Emotionalized Communication in TikTok Health Misinformation Corrections. Under Review Read →

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