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The Effect of Deepfake Video on News Credibility and Corrective Influence of Cost-Based Knowledge about Deepfakes
Digital Journalism ( IF 5.2 ) Pub Date : 2022-04-06 , DOI: 10.1080/21670811.2022.2026797
Soo Yun Shin 1 , Jiyoung Lee 2
Affiliation  

Abstract

With rapid technical advancements, deepfakes—i.e., hyper-realistic fake videos using face swaps—have become more widespread and easier to create, challenging the old notion of “seeing is believing.” Despite raised concerns over potential impacts of deepfakes on people’s credibility toward audio-visual evidence in journalism, systematic investigation of the topic has been lacking. This study conducted an experiment (N = 230) that tested (1) how a news article using deepfake video (vs. real video) affects news credibility and viral behavioral intentions and (2) whether, based on signaling theory, obtaining knowledge about the low cost of producing deepfakes reduces the impact of deepfake news. Results show that people whose pre-existing attitudes toward controversial issues (abortion, marijuana legalization) are congruent with the advocated position of a news article are more likely to believe and be willing to share deepfake news as much as real video news. In addition, educating participants about the low cost of producing deepfakes was effective in reducing the credibility and viral behavioral intention of deepfake news for those who have congruent issue attitudes. This study provides evidence for differing levels of susceptibility for deepfake news and the importance of media literacy education regarding deepfakes that would prevent biased reasoning.



中文翻译:

Deepfake 视频对新闻可信度的影响以及基于成本的 Deepfake 知识的纠正影响

摘要

随着技术的快速进步,deepfakes(即使用换脸的超现实假视频)变得更加普遍和更容易创建,挑战了“眼见为实”的旧观念。尽管人们担心深度造假对人们对新闻中视听证据的可信度的潜在影响,但一直缺乏对该主题的系统调查。本研究进行了一项实验(N = 230) 测试了 (1) 使用 deepfake 视频(与真实视频相比)的新闻文章如何影响新闻可信度和病毒行为意图,以及 (2) 基于信号理论,获得关于生产 deepfake 的低成本的知识是否会降低deepfake 新闻的影响。结果表明,那些对有争议的问题(堕胎、大麻合法化)的预先存在的态度与新闻文章所倡导的立场一致的人更有可能相信并愿意像真实的视频新闻一样分享深度假新闻。此外,对参与者进行有关制作深度伪造的低成本的教育,对于那些持有一致问题态度的人来说,有效地降低了深度伪造新闻的可信度和病毒行为意图。

更新日期:2022-04-06
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