Peer-reviewed manuscripts of research I have led or collaborated on are listed below and on Google Scholar.

Human Heuristics for AI-Generated Language Are Flawed. Maurice Jakesch, Jeff Hancock, and Mor Naaman. (2023). Proceedings of the National Academy of Sciences 120.11.
[Paper] [Pre-print] [Pre-registration] [Abstract]

Co-Writing with Opinionated Language Models Affects Users' Views. Maurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson and Mor Naaman. (2023). Proceedings of the ACM CHI.
[Paper] [Pre-print] [Abstract]

Can AI communication tools increase legislative responsiveness and trust in democratic institutions?. Sarah Kreps and Maurice Jakesch. (2023). Government Information Quarterly 40.3: 101829.
[Paper] [Abstract]

Assessing the Effects and Risks of Large Language Models in AI-Mediated Communication. Maurice Jakesch. (2023). Cornell University ProQuest Dissertations Publishing.
[PDF] [Abstract]

Comparing Sentence-Level to Message-Level Suggestions in AI-Mediated Communication. Liye Fu, Benjamin Newman, Maurice Jakesch, and Sarah Kreps. (2023). Proceedings of the ACM CHI.
[Paper] [Pre-print] [Abstract]

Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter's Trending Topics. Jospeh Schlessing, Kiran Garimella, Maurice Jakesch, and Dean Eckles. (2023). Proceedings of the AAAI ICWSM.
[Paper] [PDF] [Pre-print] [Abstract]

AHA!: Facilitating AI Impact Assessment by Generating Examples of Harms. Zana Buçinca, Chau Minh Pham, Maurice Jakesch, Marco Tulio Ribeiro, Alexandra Olteanu, and Saleema Amershi. (2023). arXiv preprint.
[Pre-print] [Abstract]

How Different Groups Prioritize Ethical Values for Responsible A.I.. Maurice Jakesch, Zana Buçinca, Saleema Amershi and Alexandra Olteanu. (2022). Proceedings of the ACM FAccT.
[Paper] [Pre-print] [Abstract]

Belief in partisan news depends on favorable content more than a trusted source. Maurice Jakesch, Mor Naaman, and Michael Macy. (2022). Under review.
[Pre-print] [Pre-registration] [Abstract]

Trend Alert: A Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election. Maurice Jakesch, Kiran Garimella, Dean Eckles, and Mor Naaman. (2021). Proceedings of the ACM CSCW.
[Paper] [Pre-print] [Abstract]

How Partisan Crowds Affect News Evaluation. Maurice Jakesch, Moran Koren, and Mor Naaman. (2020). Proceedings of the ACM TTO.
[Paper] [PDF] [Materials] [Abstract]

AI-Mediated Communication: The Perception That Profile Text Was Written by A.I. Affects Trustworthiness. Maurice Jakesch, Megan French, Xiao Ma, Jeffrey Hancock, and Mor Naaman. (2019). Proceedings of the ACM CHI.
[Paper] [Materials] [Abstract]

The Role of Source, Headline, and Expressive Responding in Political News Evaluation. Maurice Jakesch, Moran Koren, Anna Evtushenko, and Mor Naaman. (2019). Computation + Journalism Symposium.
[Paper] [Materials] [Abstract]