Artificial intelligence increasingly shapes what news people read, what content algorithms recommend, and what information people seek out through tools like ChatGPT. Yet studying these influences on human behaviour requires solving two interlinked challenges: getting the right data and being able to analyse it reliably. This talk presents data donation - where participants actively share their own digital trace data with researchers - as a key method for accessing otherwise opaque information environments. Drawing on a series of projects ranging from browser history and TikTok donations to a recent study collecting ChatGPT conversation histories, I discuss what we can learn about AI-mediated information exposure and seeking behaviour, and what remains stubbornly hard. A particular focus is the analytical challenge: when the data is messy, personal, and multi-layered/modal, how do we use computational tools - including AI itself - to make sense of it, and how much can we trust what we measure?
Dr. Felicia Loecherbach
Felicia Loecherbach is an Assistant Professor in Political Communication and Journalism at the Amsterdam School of Communication Research. Her research focuses on online news consumption, news diversity, and the use of computational methods in the social sciences. She is particularly interested in how digital information environments shape the ways people encounter, understand, and engage with news, using approaches such as digital trace data, data donations, and computational content analysis. She obtained a PhD in Computational Political Communication Science at Vrije Universiteit Amsterdam and was previously a postdoctoral fellow at the Center for Social Media and Politics at New York University.
Date: 27 May 2026
Time: 15:00
Location: NU 4B43