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Politics and porn: how news media characterizes problems presented by deepfakes.

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Title: Politics and porn: how news media characterizes problems presented by deepfakes.
Authors: Gosse, Chandell1 cgosse@uwo.ca, Burkell, Jacquelyn1
Source: Critical Studies in Media Communication. Dec2020, Vol. 37 Issue 5, p497-511. 15p.
Subject Terms: Deepfakes, Pornography, Public opinion, Journalistic reporting, Internet publishing, Press & politics
Abstract: "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. [ABSTRACT FROM AUTHOR]
Copyright of Critical Studies in Media Communication is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Politics and porn: how news media characterizes problems presented by deepfakes.
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  Data: <searchLink fieldCode="AR" term="%22Gosse%2C+Chandell%22">Gosse, Chandell</searchLink><relatesTo>1</relatesTo><i> cgosse@uwo.ca</i><br /><searchLink fieldCode="AR" term="%22Burkell%2C+Jacquelyn%22">Burkell, Jacquelyn</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="DE" term="%22Deepfakes%22">Deepfakes</searchLink><br /><searchLink fieldCode="DE" term="%22Pornography%22">Pornography</searchLink><br /><searchLink fieldCode="DE" term="%22Public+opinion%22">Public opinion</searchLink><br /><searchLink fieldCode="DE" term="%22Journalistic+reporting%22">Journalistic reporting</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+publishing%22">Internet publishing</searchLink><br /><searchLink fieldCode="DE" term="%22Press+%26+politics%22">Press & politics</searchLink>
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  Data: "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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Critical Studies in Media Communication is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/15295036.2020.1832697
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      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 497
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      – SubjectFull: Deepfakes
        Type: general
      – SubjectFull: Pornography
        Type: general
      – SubjectFull: Public opinion
        Type: general
      – SubjectFull: Journalistic reporting
        Type: general
      – SubjectFull: Internet publishing
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      – SubjectFull: Press & politics
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              Text: Dec2020
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              Y: 2020
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