Is ChatGPT scary good? How user motivations affect creepiness and trust in generative artificial intelligence
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There is a relative lack of knowledge as to why people use generative conversational AI.
“While these studies indicate that generative conversational AI can have significant implications on personal and working life, there is a relative lack of knowledge as to why people use this technology.”
From Why do people use ChatGPT? Exploring user motivations for generative conversational AI (2024) · cites this paper as Baek and Kim's (2023)
Cites
The commitment-trust theory of relationship marketing
Morgan, R. M., & Hunt, S. D. (1994) · Journal of Marketing · doi:10.1177/002224299405800302 · Cited by 22,355 · see citing works
Uses and Gratifications Research
Katz, E., Blumler, J. G., & Gurevitch, M. (1973) · Public Opinion Quarterly · doi:10.1086/268109 · Cited by 4,012 · see citing works
Uses and Gratifications Theory in the 21st Century
Ruggiero, T. E. (2000) · Mass Communication and Society · doi:10.1207/s15327825mcs0301_02 · Cited by 2,810 · see citing works
Resistance to Medical Artificial Intelligence
Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019) · Journal of Consumer Research · doi:10.1093/jcr/ucz013 · Cited by 2,015 · see citing works
Why people use social media: a uses and gratifications approach
Whiting, A., & Williams, D. (2013) · Qualitative Market Research: An International Journal · doi:10.1108/qmr-06-2013-0041 · Cited by 1,810 · see citing works
On the Use of the Mass Media for Important Things
Katz, E., Haas, H., & Gurevitch, M. (1973) · American Sociological Review · doi:10.2307/2094393 · Cited by 1,639 · see citing works
Trust in AI and Its Role in the Acceptance of AI Technologies
Choung, H., David, P., & Ross, A. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2050543 · Cited by 963 · see citing works
Feeling robots and human zombies: Mind perception and the uncanny valley
Gray, K., & Wegner, D. M. (2012) · Cognition · doi:10.1016/j.cognition.2012.06.007 · Cited by 941 · see citing works
Television uses and gratifications: The interactions of viewing patterns and motivations
Rubin, A. M. (1983) · Journal of Broadcasting · doi:10.1080/08838158309386471 · Cited by 912 · see citing works
Technology, Humanness, and Trust: Rethinking Trust in Technology
Marshall University, Lankton, N., McKnight, D. H., Michigan State University, Tripp, J., & Baylor University (2015) · Journal of the Association for Information Systems · doi:10.17705/1jais.00411 · Cited by 553 · see citing works
Cheng, X., Zhang, X., Cohen, J., & Mou, J. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.102940 · Cited by 536 · see citing works
Authentically Fake? How Consumers Respond to the Influence of Virtual Influencers
Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C., & Phua, Z. (2023) · Journal of Advertising · doi:10.1080/00913367.2022.2149641 · Cited by 506 · see citing works
Yen, C., & Chiang, M.-C. (2021) · Behaviour & Information Technology · doi:10.1080/0144929x.2020.1743362 · Cited by 297 · see citing works
Feeling our way to machine minds: people's emotions when perceiving mind in artificial intelligence
Shank, D. B., Graves, C., Gott, A., Gamez, P., & Rodriguez, S. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.04.001 · Cited by 293 · see citing works
Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot
Rajaobelina, L., Prom Tep, S., Arcand, M., & Ricard, L. (2021) · Psychology & Marketing · doi:10.1002/mar.21548 · Cited by 252 · see citing works
Park, N. (2010) · Journal of Communication · doi:10.1111/j.1460-2466.2009.01440.x · Cited by 141 · see citing works
Smiling AI agents: How anthropomorphism and broad smiles increase charitable giving
Baek, T. H., Bakpayev, M., Yoon, S., & Kim, S. (2022) · International Journal of Advertising · doi:10.1080/02650487.2021.2011654 · Cited by 125 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531 · see citing works
Wang, H., Dang, A., Wu, Z., & Mac, S. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100326 · Cited by 272 · see citing works
ChatGPT awareness, acceptance, and adoption in higher education: The role of trust as a cornerstone
Shahzad, M. F., Xu, S., & Javed, I. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00478-x · Cited by 274 · see citing works
Al-Abdullatif, A. M. (2024) · Education Sciences · doi:10.3390/educsci14111209 · Cited by 169 · see citing works
Why do people use ChatGPT? Exploring user motivations for generative conversational AI
Skjuve, M., Brandtzaeg, P. B., & Følstad, A. (2024) · First Monday · doi:10.5210/fm.v29i1.13541 · Cited by 95 · see citing works
Virvou, M., Tsihrintzis, G. A., & Tsichrintzi, E.-A. (2024) · Information Sciences · doi:10.1016/j.ins.2024.120759 · Cited by 55 · see citing works
Van Wyk, M. M. (2024) · Journal of Applied Learning and Teaching · doi:10.37074/jalt.2024.7.1.15 · Cited by 35 · see citing works
Lim, J. S., & Hong, N. (2025) · Health & New Media Research · doi:10.22720/hnmr.2025.00115 · Cited by 6 · see citing works
- Authors
- Hyun Baek, T., & Kim, M.
- Affiliations
- Louisiana State University (US)
- Corresponding author
- Kim, Minseong
- ORCID
- Kim, Minseong
- Venue
- Telematics and Informatics
- Publisher
- Elsevier BV
- Published
- 2023-09
- Volume
- 83
- Pages
- 102030
- ISSN
- 0736-5853 (ISSN-L)
- OpenAlex
- W4385484115
- Cited by
- 319
- References
- 17
- Citations by year
- 2026: 91 · 2025: 127 · 2024: 97 · 2023: 4
- FWCI
- 30.07
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Telematics and Informatics (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- ChatGPT, generative AI, user motivation, creepiness, trust in AI, continuance intention, personalization, task efficiency, social interaction, AI chatbots, user interface design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review