| AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness M Jakesch, M French, X Ma, JT Hancock, M Naaman Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2019 | 177 | 2019 |
| Co-writing with opinionated language models affects users’ views M Jakesch, A Bhat, D Buschek, L Zalmanson, M Naaman Proceedings of the 2023 CHI conference on human factors in computing systems …, 2023 | 176 | 2023 |
| Human heuristics for AI-generated language are flawed M Jakesch, JT Hancock, M Naaman Proceedings of the National Academy of Sciences 120 (11), e2208839120, 2023 | 161 | 2023 |
| How different groups prioritize ethical values for responsible AI M Jakesch, Z Buçinca, S Amershi, A Olteanu Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 94 | 2022 |
| The Role of Source, Headline and Expressive Responding in Political News Evaluation M Jakesch, M Koren, A Evtushenko, M Naaman Computation and Journalism Symposium 2019, 2019 | 38 | 2019 |
| Trend alert: A cross-platform organization manipulated Twitter trends in the Indian general election M Jakesch, K Garimella, D Eckles, M Naaman Proceedings of the ACM on Human-computer Interaction 5 (CSCW2), 1-19, 2021 | 36 | 2021 |
| Aha!: Facilitating ai impact assessment by generating examples of harms Z Buçinca, CM Pham, M Jakesch, MT Ribeiro, A Olteanu, S Amershi arXiv preprint arXiv:2306.03280, 2023 | 20 | 2023 |
| Comparing sentence-level suggestions to message-level suggestions in AI-mediated communication L Fu, B Newman, M Jakesch, S Kreps Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023 | 16 | 2023 |
| AI Writing Assistants Influence Topic Choice in Self-Presentation R Poddar, R Sinha, M Naaman, M Jakesch Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023 | 10 | 2023 |
| Can AI communication tools increase legislative responsiveness and trust in democratic institutions? S Kreps, M Jakesch Government Information Quarterly 40 (3), 101829, 2023 | 8 | 2023 |
| Fears about AI-mediated communication are grounded in different expectations for one's own versus others' use ZA Purcell, M Dong, AM Nussberger, N Köbis, M Jakesch arXiv preprint arXiv:2305.01670, 2023 | 6 | 2023 |
| Bias in AI Autocomplete Suggestions Leads to Attitude Shift on Societal Issues S Williams-Ceci, M Jakesch, A Bhat, K Kadoma, L Zalmanson, M Naaman, ... PsyArXiv, 2024 | 4 | 2024 |
| Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter’s Trending Topics J Schlessinger, K Garimella, M Jakesch, D Eckles Proceedings of the International AAAI Conference on Web and Social Media 17 …, 2023 | 1 | 2023 |
| Belief in partisan news depends on favorable content more than on a trusted source M Jakesch, M Naaman, M Michael PsyArXiv, 2022 | 1 | 2022 |
| How Partisan Crowds Affect News Evaluation M Jakesch, M Koren, A Evtushenko, M Naaman Proceedings of the 2020 Conference for Truth and Trust Online, 2020 | 1 | 2020 |
| People have different expectations for their own versus others' use of AI‐mediated communication tools ZA Purcell, M Dong, AM Nussberger, N Köbis, M Jakesch British Journal of Psychology, 2024 | | 2024 |
| Trust in AI in Under-resourced Environments: Lessons from Local Journalism MA Le Quéré, M Jakesch CHI'22 TRAIT: Workshop on Trust and Reliance in AI-Human Teams, 2022 | | 2022 |
Mor NaamanProfessor, Cornell TechVerified email at cornell.edu
