Deepfake crimes in the age of AI: A bibliometric study of emerging risks and research trends

This study presents a bibliometric analysis of scholarly research on deepfake crimes in the age of AI, examining emerging risks and research trends between 2019 and 2025. Drawing on 349 publications from the Web of Science Core Collection, the study uses VOSviewer to map publication patterns, collaboration networks, and thematic clusters. The results reveal that research on deepfake crimes is very interdisciplinary, as AI-based detection studies are increasingly intersecting with legal, social, and criminal discussions. The cluster analysis highlights that while significant progress has been made in technical detection methods, there are still serious gaps in addressing the societal harms of misinformation and non-consensual content. These results indicate that the field is not only growing rapidly, but is also moving towards a more integrated agenda that combines technological innovation with ethical and regulatory considerations. The study contributes theoretically by framing deep counterfeiting as technological and criminal phenomena, and practically by providing insights to policy makers, researchers and practitioners seeking to mitigate the societal and security risks of artificial media.