Marianne Aubin Le Quéré

Human-computer interaction; social computing; computational social science; communication and journalism; information ecosystems; credibility and provenance; AI-mediated communication; human-AI interaction; social media; computational measurement and text analysis

• Princeton Data-Driven Social Science Interim Research Grant (2025)
• Public Voices Fellow on Technology in the Public Interest (2025)
• NY Public Interest Technology Regional Seed Grant (2025)
• Top Paper Award, International Communication Association Conference, Communication and Technology Division (2024)
• Digital Life Initiative Doctoral Fellowship (2021)
• Facebook Fellowship Finalist in Computational Social Science (2021)

Marianne Aubin Le Quéré is an assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign, where she runs the Future of Information Lab (FOiL). Previously, she was a Postdoctoral Research Fellow at Princeton's Center for Information Technology Policy from 2025 to 2026. Her work traces how AI and other emerging technologies impact news and civic information ecosystems to help keep the public informed and civically engaged in an accessible, transparent, and equitable way. Her research bridges human-computer interaction, computational social science, and communication and has been published in top-tier computer science conferences, general science venues, and communication journals. She was also named a Public Voices Fellow on Technology in the Public Interest, and her work has received a Top Paper award in the Communication and Technology Division of the International Communication Association Conference. She earned her PhD in Information Science from Cornell University in 2025. 

El Malki, O., Aubin Le Quéré, M., Monroy-Hernández, A., Horta Ribeiro, M. Bonsai: Intentional and Personalized Social Media Feeds. Accepted to the ACM (Association of Computing Machinery) CHI conference on Human Factors in Computing Systems, 2026.

Tseng, E., Young, M., Aubin Le Quéré, M., Reinhart, A., Suresh, H. “Ownership, Not Just Happy Talk:” Co-Designing a Participatory Large Language Model for Journalism. Accepted to the ACM Conference on Fairness, Accountability, and Transparency, 2025.

Aubin Le Quéré, M., Kairam, S. (2025) Welcome to the Neighborhood: Assessing Localized Social Media Use and Pro-Community Attitudes in a Multi-National Survey. Social Media & Society.

Aubin Le Quéré, M*., Randazzo, C., Mimno, D., Schoenebeck, S. (2025). Large Language Models in Qualitative Research: Uses, Tensions, and Intentional Choices Hope Schroeder. Accepted to ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), 2025.

Aubin LeQuéré, M*., Matias, J*. (2025). When Curiosity Gaps Backfire: Effects of Headline Concreteness on Information Selection Decisions. Nature Scientific Reports.

Aubin Le Quéré, M., Chiang, T., Naaman, M. (2022). Understanding Local News Social Coverage and Engagement at Scale During the COVID-19 Pandemic  International Conference on Web and Social Media (ICWSM).

Choksi, M*., Aubin Le Quéré, M*., Lloyd, T., Tao, R., Grimmelmann, J., Naaman, M. (2024). Under the (Neighbor)hood: Hyperlocal Surveillance on Nextdoor. Proceedings, the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI).

Aubin Le Quéré, M., Fields, J., Naaman, M. (2024). Not Quite Filling the Void: Comparing the Perceptions of Local Online Groups and Local Media Pages on Facebook. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1).

Aubin Le Quéré, M., Chiang, T., Levy, K., Naaman, M. (2022). Information Needs of Essential Workers During the COVID-19 Pandemic  Proceedings of the ACM on Human-Computer Interaction 6(CSCW2).

Matias*, J*., Munger*, K*., Aubin Le Quéré, M*, Ebersole, C*. (2021). The Upworthy Research Archive, a time series of 32,487 experiments in U.S. media. Nature Scientific Data.

Aligning Epistemic Processes and Audience Perceptions for News Consumption, Princeton Center for Information Technology Policy Seminar, 2026

Panel on AI Search and News, Tow Center for Digital Journalism at Columbia University, 2026

Qualitative Analysis and Large Language Models, National Centre for Research Methods, 2025

Towards Identifying Local Content Deserts with Open-Source Large Language Models, Computation and Journalism 2024