
doi: 10.1093/jcmc/zmac008
AbstractDeepfake 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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 69 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
