The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016
Abstract
This study examines the agenda-setting power of fake news and fact-checkers who fight them through a computational look at the online mediascape from 2014 to 2016. Although our study confirms that content from fake news websites is increasing, these sites do not exert excessive power. Instead, fake news has an intricately entwined relationship with online partisan media, both responding and setting its issue agenda. In 2016, partisan media appeared to be especially susceptible to the agendas of fake news, perhaps due to the election. Emerging news media are also responsive to the agendas of fake news, but to a lesser degree. Fake news coverage itself is diverging and becoming more autonomous topically. While fact-checkers are autonomous in their selection of issues to cover, they were not influential in determining the agenda of news media overall, and their influence appears to be declining, illustrating the difficulties fact-checkers face in disseminating their corrections.
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The psychological drivers of misinformation belief and its resistance to correction
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Metadata
- Authors
- Vargo, C. J., Guo, L., & Amazeen, M. A.
- Venue
- New Media & Society
- Publisher
- SAGE Publications
- Published
- 2017-06-15
- Volume
- 20
- Issue
- 5
- Pages
- 2028-2049
- ISSN
- 1461-4448 (ISSN-L)
- 1461-7315
- OpenAlex
- W2626653630
- Cited by
- 624
- References
- 20
- FWCI
- 147.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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- Vargo, C. J., Guo, L., & Amazeen, M. A. (2018). The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016. New Media & Society. https://doi.org/10.1177/1461444817712086
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
