The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
The diffusion of misinformation on social media: Temporal pattern, message, and source
Open accessAbstract
This study examines dynamic communication processes of political misinformation on social media focusing on three components: the temporal pattern, content mutation, and sources of misinformation. We traced the lifecycle of 17 popular political rumors that circulated on Twitter over 13 months during the 2012 U.S. presidential election. Using text analysis based on time series, we found that while false rumors (misinformation) tend to come back multiple times after the initial publication, true rumors (facts) do not. Rumor resurgence continues, often accompanying textual changes, until the tension around the target dissolves. We observed that rumors resurface by partisan news websites that repackage the old rumor into news and, gain visibility by influential Twitter users who introduce such rumor into the Twittersphere. In this paper, we argue that media scholars should consider the mutability of diffusing information, temporal recurrence of such messages, and the mechanism by which these messages evolve over time. False political rumors tend to resurface multiple times after the initial publication.False political rumors often turn into a more intense and extreme version over time.Resurged old political rumors tend to be presented as news.None-traditional partisan media are often behind the constant generation of false news.
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Cites
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Cited by
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Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373
Fake online reviews: Literature review, synthesis, and directions for future research
Wu, Y., Ngai, E. W. T., Wu, P., & Wu, C. (2020) · Decision Support Systems · doi:10.1016/j.dss.2020.113280 · Cited by 359
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284
Jerit, J., & Zhao, Y. (2020) · Annual Review of Political Science · doi:10.1146/annurev-polisci-050718-032814 · Cited by 263
Naeem, M., & Ozuem, W. (2022) · Information Technology & People · doi:10.1108/itp-01-2021-0061 · Cited by 94
Metadata
- Authors
- Shin, J., Jian, L., Driscoll, K., & Bar, F.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 83
- Pages
- 278-287
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2793246835
- Cited by
- 401
- References
- 57
- FWCI
- 98.53
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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