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Politics and porn: how news media characterizes problems presented by deepfakes
Open accessAbstract
“Deepfake” is a form of machine learning that creates fake videos by superimposing the face of one person on to the body of another in a new video. The technology has been used to create non-consensual fake pornography and sexual imagery, but there is concern that it will soon be used for politically nefarious ends. This study seeks to understand how the news media has characterized the problem(s) presented by deepfakes. We used discourse analysis to examine news articles about deepfakes, finding that news media discuss the problems of deepfakes in four ways: as (too) easily produced and distributed; as creating false beliefs; as undermining the political process; and as non-consensual sexual content. We provide an overview of how news media position each problem followed by a discussion about the varying degrees of emphasis given to each problem and the implications this has for the public’s perception and construction of deepfakes.
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Metadata
- Authors
- Gosse, C., & Burkell, J.
- Affiliations
- Western University (CA)
- Corresponding author
- Gosse, Chandell
- Venue
- Critical Studies in Media Communication
- Publisher
- Informa UK Limited
- Published
- 2020-10-19
- Volume
- 37
- Issue
- 5
- Pages
- 497-511
- ISSN
- 1479-5809 (ISSN-L)
- 1529-5036
- OpenAlex
- W3094359535
- Cited by
- 148
- References
- 23
- Citations by year
- 2026: 18 · 2025: 19 · 2024: 19 · 2023: 69 · 2022: 19 · 2021: 2 · 2020: 1
- FWCI
- 30.36
- Type
- journal article
- Language
- en
- Open access
- green
- ir.lib.uwo.ca
- Locations
- Critical Studies in Media Communication (publishedVersion)
- Scholarship@Western (Western University) (submittedVersion)
- Funders
- Social Sciences and Humanities Research Council of Canada (895-2015-1002)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › News Media Framing and Political Communication
- Social Sciences › Gender Studies › Gender, Feminism, and Media
- Keywords
- deepfakes, news framing, political manipulation, misinformation, public perception, media discourse
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 ›
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