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To Believe or Not to Believe: Framing Analysis of Content and Audience Response of Top 10 Deepfake Videos on YouTube.
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- Author(s): Lee Y;Lee Y; Huang KT; Huang KT; Blom R; Blom R; Schriner R; Schriner R; Ciccarelli CA; Ciccarelli CA
- Source:
Cyberpsychology, behavior and social networking [Cyberpsychol Behav Soc Netw] 2021 Mar; Vol. 24 (3), pp. 153-158. Date of Electronic Publication: 2021 Feb 17.- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 101528721 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2152-2723 (Electronic) Linking ISSN: 21522715 NLM ISO Abbreviation: Cyberpsychol Behav Soc Netw Subsets: MEDLINE
- Publication Information: Original Publication: New Rochelle, NY : Mary Ann Liebert, Inc.
- Subject Terms:
- Abstract: This study explores popular deepfake media content and audience response in an effort to gain better understanding of the potential social and psychological impacts of deepfakes. A content analysis of the top 10 YouTube deepfake videos and their audience comments ( n = 2,689) was conducted to investigate the degree to which media meta-frame influenced audience response. The results suggested that media meta-frame, the type of video (deepfake videos with commentaries or original deepfake videos), and the number of dislikes on the video had considerable influence on audience response (attitudes and perceived realism), while the majority of the audience expressed neutral or irrelevant attitudes. Our exploratory observation revealed a dynamic interplay of how deepfake was presented and how others react to it might influence the public. Thus, it is necessary to appropriately caution the public about their vulnerability to the ever-advancing deepfake technologies.
- Contributed Indexing: Keywords: YouTube; audience; deepfakes; framing
- Publication Date: Date Created: 20210218 Date Completed: 20210611 Latest Revision: 20210611
- Publication Date: 20240105
- Accession Number: 10.1089/cyber.2020.0176
- Accession Number: 33600225
- Source:
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