{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T02:57:45Z","timestamp":1772593065777,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T00:00:00Z","timestamp":1745539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,4,26]]},"DOI":"10.1145\/3706599.3716299","type":"proceedings-article","created":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T20:40:13Z","timestamp":1745440813000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Human Subjects Research in the Age of Generative AI: Opportunities and Challenges of Applying LLM-Simulated Data to HCI Studies"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0951-7845","authenticated-orcid":false,"given":"Angel Hsing-Chi","family":"Hwang","sequence":"first","affiliation":[{"name":"University of Southern California, Los Angeles, California, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8020-9434","authenticated-orcid":false,"given":"Michael S.","family":"Bernstein","sequence":"additional","affiliation":[{"name":"Stanford University, Stanford, California, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5779-8864","authenticated-orcid":false,"given":"S. Shyam","family":"Sundar","sequence":"additional","affiliation":[{"name":"Media Effects Research Laboratory, Penn State University, University Park, Pennsylvania, USA and Sungkyunkwan University, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7636-9598","authenticated-orcid":false,"given":"Renwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Communications and New Media, National University of Singapore, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6159-9657","authenticated-orcid":false,"given":"Manoel","family":"Horta Ribeiro","sequence":"additional","affiliation":[{"name":"Princeton University, Princeton, New Jersey, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9955-6070","authenticated-orcid":false,"given":"Yingdan","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Communication Studies, School of Communication, Northwestern University, Evanston, Illinois, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4253-1016","authenticated-orcid":false,"given":"Serina","family":"Chang","sequence":"additional","affiliation":[{"name":"EECS &amp; Computational Precision Health, University of California, Berkeley, Berkeley, California, USA and Microsoft Research, New York City, New York, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1630-0588","authenticated-orcid":false,"given":"Tongshuang","family":"Wu","sequence":"additional","affiliation":[{"name":"Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3756-7812","authenticated-orcid":false,"given":"Aimei","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, California, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7995-4429","authenticated-orcid":false,"given":"Dmitri","family":"Williams","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, California, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5036-4409","authenticated-orcid":false,"given":"Joon Sung","family":"Park","sequence":"additional","affiliation":[{"name":"Computer Science Department, Stanford University, Stanford, California, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3038-7077","authenticated-orcid":false,"given":"Katherine","family":"Ognyanova","sequence":"additional","affiliation":[{"name":"School of Communication &amp; Information, Rutgers University, New Brunswick, New Jersey, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3368-0180","authenticated-orcid":false,"given":"Ziang","family":"Xiao","sequence":"additional","affiliation":[{"name":"Johns Hopkins University, Baltimore, Maryland, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4330-957X","authenticated-orcid":false,"given":"Aaron","family":"Shaw","sequence":"additional","affiliation":[{"name":"Northwestern University, Evanston, Illinois, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2399-9374","authenticated-orcid":false,"given":"David A.","family":"Shamma","sequence":"additional","affiliation":[{"name":"Toyota Research Institute, Los Altos, California, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,4,25]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"publisher","unstructured":"Lisa\u00a0P. Argyle Ethan\u00a0C. Busby Nancy Fulda Joshua\u00a0R. Gubler Christopher Rytting and David Wingate. 2023. Out of One Many: Using Language Models to Simulate Human Samples. Political Analysis 31 3 (July 2023) 337\u2013351. 10.1017\/pan.2023.2","DOI":"10.1017\/pan.2023.2"},{"key":"e_1_3_3_2_3_2","first-page":"2589","volume-title":"Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)","author":"Beck Tilman","year":"2024","unstructured":"Tilman Beck, Hendrik Schuff, Anne Lauscher, and Iryna Gurevych. 2024. Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), Yvette Graham and Matthew Purver (Eds.). Association for Computational Linguistics, St. Julian\u2019s, Malta, 2589\u20132615. https:\/\/aclanthology.org\/2024.eacl-long.159"},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"publisher","unstructured":"James Bisbee Joshua\u00a0D. Clinton Cassy Dorff Brenton Kenkel and Jennifer\u00a0M. Larson. 2024. Synthetic Replacements for Human Survey Data? The Perils of Large Language Models. Political Analysis 32 4 (Oct. 2024) 401\u2013416. 10.1017\/pan.2024.5","DOI":"10.1017\/pan.2024.5"},{"key":"e_1_3_3_2_5_2","doi-asserted-by":"publisher","unstructured":"Serina Chang Alicja Chaszczewicz Emma Wang Maya Josifovska Emma Pierson and Jure Leskovec. 2024. LLMs generate structurally realistic social networks but overestimate political homophily. arXiv:2408.16629 (Aug. 2024). 10.48550\/arXiv.2408.16629 arXiv:https:\/\/arXiv.org\/abs\/2408.16629 [cs].","DOI":"10.48550\/arXiv.2408.16629"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.84"},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.669"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"publisher","unstructured":"Dorottya Demszky Diyi Yang David\u00a0S. Yeager Christopher\u00a0J. Bryan Margarett Clapper Susannah Chandhok Johannes\u00a0C. Eichstaedt Cameron Hecht Jeremy Jamieson Meghann Johnson Michaela Jones Danielle Krettek-Cobb Leslie Lai Nirel JonesMitchell Desmond\u00a0C. Ong Carol\u00a0S. Dweck James\u00a0J. Gross and James\u00a0W. Pennebaker. 2023. Using large language models in psychology. Nature Reviews Psychology 2 11 (Nov. 2023) 688\u2013701. 10.1038\/s44159-023-00241-5","DOI":"10.1038\/s44159-023-00241-5"},{"key":"e_1_3_3_2_9_2","doi-asserted-by":"publisher","unstructured":"Rodney\u00a0A. Gabriel Onkar Litake Sierra Simpson Brittany\u00a0N. Burton Ruth\u00a0S. Waterman and Alvaro\u00a0A. Macias. 2024. On the development and validation of large language model-based classifiers for identifying social determinants of health. Proceedings of the National Academy of Sciences 121 39 (2024) e2320716121. 10.1073\/pnas.2320716121 arXiv:https:\/\/www.pnas.org\/doi\/pdf\/10.1073\/pnas.2320716121","DOI":"10.1073\/pnas.2320716121"},{"key":"e_1_3_3_2_10_2","doi-asserted-by":"publisher","unstructured":"Igor Grossmann Matthew Feinberg Dawn\u00a0C. Parker Nicholas\u00a0A. Christakis Philip\u00a0E. Tetlock and William\u00a0A. Cunningham. 2023. AI and the transformation of social science research. Science 380 6650 (June 2023) 1108\u20131109. 10.1126\/science.adi1778","DOI":"10.1126\/science.adi1778"},{"key":"e_1_3_3_2_11_2","doi-asserted-by":"publisher","unstructured":"George Gui and Olivier Toubia. 2023. The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective. SSRN Electronic Journal (2023). 10.2139\/ssrn.4650172 arXiv:https:\/\/arXiv.org\/abs\/2312.15524 [cs econ stat].","DOI":"10.2139\/ssrn.4650172"},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"publisher","unstructured":"John\u00a0J. Horton. 2023. Large Language Models as Simulated Economic Agents: What Can We Learn from Homo Silicus?31122 (April 2023). 10.3386\/w31122 DOI: 10.3386\/w31122.","DOI":"10.3386\/w31122"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"publisher","unstructured":"Q.\u00a0Vera Liao and Ziang Xiao. 2023. Rethinking Model Evaluation as Narrowing the Socio-Technical Gap. arXiv:2306.03100 (June 2023). 10.48550\/arXiv.2306.03100 arXiv:https:\/\/arXiv.org\/abs\/2306.03100.","DOI":"10.48550\/arXiv.2306.03100"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-short.88"},{"key":"e_1_3_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3586183.3606763"},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3526113.3545616"},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"publisher","unstructured":"Joon\u00a0Sung Park Carolyn\u00a0Q. Zou Aaron Shaw Benjamin\u00a0Mako Hill Carrie Cai Meredith\u00a0Ringel Morris Robb Willer Percy Liang and Michael\u00a0S. Bernstein. 2024. Generative Agent Simulations of 1 000 People. arXiv:2411.10109 (Nov. 2024). 10.48550\/arXiv.2411.10109 arXiv:https:\/\/arXiv.org\/abs\/2411.10109.","DOI":"10.48550\/arXiv.2411.10109"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"publisher","unstructured":"Peter\u00a0S. Park Philipp Schoenegger and Chongyang Zhu. 2023. Diminished Diversity-of-Thought in a Standard Large Language Model. arXiv:2302.07267 (Sept. 2023). 10.48550\/arXiv.2302.07267 arXiv:https:\/\/arXiv.org\/abs\/2302.07267 [cs].","DOI":"10.48550\/arXiv.2302.07267"},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613905.3636293"},{"key":"e_1_3_3_2_20_2","doi-asserted-by":"publisher","unstructured":"Steve Rathje Dan-Mircea Mirea Ilia Sucholutsky Raja Marjieh Claire\u00a0E. Robertson and Jay J.\u00a0Van Bavel. 2024. GPT is an effective tool for multilingual psychological text analysis. Proceedings of the National Academy of Sciences 121 34 (2024) e2308950121. 10.1073\/pnas.2308950121 arXiv:https:\/\/www.pnas.org\/doi\/pdf\/10.1073\/pnas.2308950121","DOI":"10.1073\/pnas.2308950121"},{"key":"e_1_3_3_2_21_2","series-title":"(ICML\u201923)","volume-title":"Proceedings of the 40th International Conference on Machine Learning","author":"Santurkar Shibani","year":"2023","unstructured":"Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, and Tatsunori Hashimoto. 2023. Whose opinions do language models reflect?. In Proceedings of the 40th International Conference on Machine Learning (Honolulu, Hawaii, USA) (ICML\u201923). JMLR.org, Article 1244, 34\u00a0pages."},{"key":"e_1_3_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642096"},{"key":"e_1_3_3_2_23_2","volume-title":"The MAIN model: A heuristic approach to understanding technology effects on credibility","author":"Sundar S\u00a0Shyam","year":"2008","unstructured":"S\u00a0Shyam Sundar. 2008. The MAIN model: A heuristic approach to understanding technology effects on credibility. MacArthur Foundation Digital Media and Learning Initiative Cambridge, MA."},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","unstructured":"S\u00a0Shyam Sundar. 2020. Rise of Machine Agency: A Framework for Studying the Psychology of Human\u2013AI Interaction (HAII). Journal of Computer-Mediated Communication 25 1 (March 2020) 74\u201388. 10.1093\/jcmc\/zmz026","DOI":"10.1093\/jcmc\/zmz026"},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1002\/9781118426456.ch3"},{"key":"e_1_3_3_2_26_2","doi-asserted-by":"publisher","unstructured":"Lindia Tjuatja Valerie Chen Tongshuang Wu Ameet Talwalkwar and Graham Neubig. 2024. Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design. Transactions of the Association for Computational Linguistics 12 (Sept. 2024) 1011\u20131026. 10.1162\/tacla00685","DOI":"10.1162\/tacla00685"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","unstructured":"Veniamin Veselovsky Manoel\u00a0Horta Ribeiro Philip Cozzolino Andrew Gordon David Rothschild and Robert West. 2023. Prevalence and prevention of large language model use in crowd work. arXiv:2310.15683 (Oct. 2023). 10.48550\/arXiv.2310.15683 arXiv:https:\/\/arXiv.org\/abs\/2310.15683 [cs].","DOI":"10.48550\/arXiv.2310.15683"},{"key":"e_1_3_3_2_28_2","doi-asserted-by":"publisher","unstructured":"Angelina Wang Jamie Morgenstern and John\u00a0P. Dickerson. 2024. Large language models should not replace human participants because they can misportray and flatten identity groups. arXiv:2402.01908 (Sept. 2024). 10.48550\/arXiv.2402.01908 arXiv:https:\/\/arXiv.org\/abs\/2402.01908 [cs].","DOI":"10.48550\/arXiv.2402.01908"},{"key":"e_1_3_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642466"},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"publisher","unstructured":"Dmitri Williams Euna\u00a0Mehnaz Khan Nishith Pathak and Jaideep Srivastava. 2023. Social Value: A Computational Model for Measuring Influence on Purchases and Actions for Individuals and Systems. Journal of Advertising 52 2 (March 2023) 247\u2013263. 10.1080\/00913367.2021.2002743","DOI":"10.1080\/00913367.2021.2002743"},{"key":"e_1_3_3_2_31_2","doi-asserted-by":"publisher","unstructured":"Tongshuang Wu Haiyi Zhu Maya Albayrak Alexis Axon Amanda Bertsch Wenxing Deng Ziqi Ding Bill Guo Sireesh Gururaja Tzu-Sheng Kuo Jenny\u00a0T. Liang Ryan Liu Ihita Mandal Jeremiah Milbauer Xiaolin Ni Namrata Padmanabhan Subhashini Ramkumar Alexis Sudjianto Jordan Taylor Ying-Jui Tseng Patricia Vaidos Zhijin Wu Wei Wu and Chenyang Yang. 2023. LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs. arXiv:2307.10168 (July 2023). 10.48550\/arXiv.2307.10168 arXiv:https:\/\/arXiv.org\/abs\/2307.10168.","DOI":"10.48550\/arXiv.2307.10168"},{"key":"e_1_3_3_2_32_2","doi-asserted-by":"publisher","unstructured":"Aimei Yang and Dmitri Williams. 2024. Quantifying Networked Influence: How Much Do Disinformation Spreaders\u2019 Networks Drive Their Public Engagement Outcomes? Social Media + Society 10 3 (July 2024) 20563051241265865. 10.1177\/20563051241265865","DOI":"10.1177\/20563051241265865"}],"event":{"name":"CHI EA '25: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems","location":"Yokohama Japan","acronym":"CHI EA '25","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706599.3716299","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3706599.3716299","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:43Z","timestamp":1750295923000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706599.3716299"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,25]]},"references-count":31,"alternative-id":["10.1145\/3706599.3716299","10.1145\/3706599"],"URL":"https:\/\/doi.org\/10.1145\/3706599.3716299","relation":{},"subject":[],"published":{"date-parts":[[2025,4,25]]},"assertion":[{"value":"2025-04-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}