From verification to virality: Psychological and behavioral drivers of engagement with perceived non-malicious deepfakes

Abstract

Deepfakes, AI-generated media that modify images, videos, or audio, represent a rapidly expanding digital phenomenon. While prior research has emphasized deepfakes in misinformation, limited attention has been given to user interaction with non-malicious deepfakes. This study employs the Approach–Avoidance Motivation Framework to examine motivational orientations and applies Goal Framing Theory to assess normative, hedonic, and gain motivations. Findings indicate that social media news use and skepticism positively predict verification intentions, whereas government engagement does not. Perceptions of reasonable use and non-deceptiveness influence ethical acceptability, which does not significantly predict viral behavioral intention. Perceived enjoyment, gain motivation, and verification intentions positively affect viral behavioral intention toward educational and entertainment-oriented non-malicious deepfakes, with gain motivation exerting a stronger effect among highly conscientious individuals. These results advance theoretical understanding of user engagement with synthetic media and suggest that governance and digital literacy initiatives should differentiate educational and entertainment-oriented non-malicious deepfakes from higher-risk forms, balancing creative engagement with transparency and responsible use.