The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A Robot Wrote This?: How perceived machine authorship affects news credibility
Abstract
As more news articles are written via collaboration between journalists and algorithms, questions have arisen regarding how automation influences the way that news is processed and evaluated by audiences. Informed by expectancy violation theory and the MAIN model, two experimental studies were conducted that examined the effect of purported machine authorship on perceptions of news credibility. Study One (N = 129) revealed that news attributed to a machine is perceived as less credible than news attributed to a human journalist. Study Two (N = 182) also observed negative effects of machine authorship through the indirect pathway of source anthropomorphism and negative expectancy violations, with evidence of moderation by prior recall of robotics also observed. The theoretical and practical implications of these findings are discussed.
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Citations
Cites
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022 · cited 1×
“…expectancy violation effects might also be elicited by the metaphors used to describe automation (e.g. “robot reporter”), as the act of anthropomorphizing technology can heighten users’ subsequent expectations of entities’ social abilities (e.g. Nass 2011; Nass and Moon 2000; Reeves and Nass 1996).”
BackgroundBartneck, C., Kulić, D., Croft, E., & Zoghbi, S. (2009) · International Journal of Social Robotics · doi:10.1007/s12369-008-0001-3 · Cited by 3,193
Carlson, M. (2015) · Digital Journalism · doi:10.1080/21670811.2014.976412 · Cited by 542
Cited by
AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations
Hancock, J. T., Naaman, M., & Levy, K. (2020) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmz022 · Cited by 658
Jakesch, M., French, M., Ma, X., Hancock, J. T., & Naaman, M. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300469 · Cited by 190
Graefe, A., & Bohlken, N. (2020) · Media and Communication · doi:10.17645/mac.v8i3.3019 · Cited by 154
“9 Waddell 1 612 47 38 USA Commercial online English X Khan Conflict, 3 (attribution) × X X X 7 (2019b) panel (Amazon Paris Accord 2 (media outlet) × Mechanical Turk) 2 (topic)”
BackgroundWu, L., & Jing Wen, T. (2021) · Journal of Advertising Research · doi:10.2501/jar-2021-004 · Cited by 127
Hong, J. W., Peng, Q., & Williams, D. (2021) · New Media & Society · doi:10.1177/1461444820925798 · Cited by 102
Metadata
- Authors
- Waddell, T. F.
- Venue
- Digital Journalism
- Publisher
- Informa UK Limited
- Published
- 2017-10-20
- Volume
- 6
- Issue
- 2
- Pages
- 236-255
- ISSN
- 2167-0811 (ISSN-L)
- 2167-082X
- OpenAlex
- W2765085847
- Cited by
- 169
- References
- 3
- FWCI
- 16.61
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
