The detection of political deepfakes
Dublin Core
Title
The detection of political deepfakes
Subject
political deepfakes, misinformation, fake news, analytic thinking, artificial intelligence
Description
Deepfake technology, allowing manipulations of audiovisual content by means of artificial intelligence, is on the rise. This has sparked concerns about a weaponization of manipulated videos for malicious ends. A theory on deepfake detection is presented and three preregistered studies examined the detection of deepfakes in the political realm (featuring UK’s Prime Minister Boris Johnson, Studies 1–3, or former U.S. President Barack Obama, Study 2). Based on two system models of information processing as well as recent theory and research on fake news, individual
differences in analytic thinking and political interest were examined as predictors of correctly detecting deepfakes. Analytic thinking (Studies 1 and 2) and political interest (Study 1) were positively associated with identifying deepfakes and negatively associated with the perceived accuracy of a fake news piece about a leaked video (whether or not the deepfake video itself was presented, Study 3). Implications for research and practice are discussed.
differences in analytic thinking and political interest were examined as predictors of correctly detecting deepfakes. Analytic thinking (Studies 1 and 2) and political interest (Study 1) were positively associated with identifying deepfakes and negatively associated with the perceived accuracy of a fake news piece about a leaked video (whether or not the deepfake video itself was presented, Study 3). Implications for research and practice are discussed.
Creator
Markus Appel, Fabian Prietzel
Source
https://doi.org/10.1093/jcmc/zmac008
Publisher
Oxford University Press
Date
21 April 2022
Contributor
Sri Wahyuni
Format
PDF
Language
English
Type
Text
Coverage
Journal of Computer-Mediated Communication, 2022
Files
Collection
Citation
Markus Appel, Fabian Prietzel, “The detection of political deepfakes,” Repository Horizon University Indonesia, accessed May 21, 2025, https://repository.horizon.ac.id/items/show/8753.