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A Contemporary and Comprehensive Bibliometric Exposition on Deepfake Research and Trends

Akanbi Bolakale AbdulQudus¹, Oluwatosin Ahmed Amodu^2,3,*, Umar Ali Bukar⁴, Raja Azlina Raja Mahmood², Anies Faziehan Zakaria⁵, Saki-Ogah Queen⁶, Zurina Mohd Hanapi²

1 Department of Mathematics and Computer Science, Elizade University, Ilara-Mokin, 340271, Nigeria
2 Department of Communication Technology and Network, Universiti Putra Malaysia (UPM), Serdang, 43400, Malaysia
3 Information and Communication Engineering Department, Elizade University, Ilara-Mokin, 340271, Nigeria
4 Department of Computer Science, Faculty of Computing and Artificial Intelligence, Taraba State University, ATC, Jalingo, 660213, Nigeria
5 Department of Engineering Education, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, 43600, Selangor, Malaysia
6 Department of Applied Modelling and Quantitative Methods, Trent University, Peterborough, ON K9L 0G2, Canada

* Corresponding Author: Oluwatosin Ahmed Amodu. Email:

Computers, Materials & Continua 2025, 84(1), 153-236. https://doi.org/10.32604/cmc.2025.061427

Received 24 November 2024; Accepted 07 April 2025; Issue published 09 June 2025

Abstract

This paper provides a comprehensive bibliometric exposition on deepfake research, exploring the intersection of artificial intelligence and deepfakes as well as international collaborations, prominent researchers, organizations, institutions, publications, and key themes. We performed a search on the Web of Science (WoS) database, focusing on Artificial Intelligence and Deepfakes, and filtered the results across 21 research areas, yielding 1412 articles. Using VOSviewer visualization tool, we analyzed this WoS data through keyword co-occurrence graphs, emphasizing on four prominent research themes. Compared with existing bibliometric papers on deepfakes, this paper proceeds to identify and discuss some of the highly cited papers within these themes: deepfake detection, feature extraction, face recognition, and forensics. The discussion highlights key challenges and advancements in deepfake research. Furthermore, this paper also discusses pressing issues surrounding deepfakes such as security, regulation, and datasets. We also provide an analysis of another exhaustive search on Scopus database focusing solely on Deepfakes (while not excluding AI) revealing deep learning as the predominant keyword, underscoring AI’s central role in deepfake research. This comprehensive analysis, encompassing over 500 keywords from 8790 articles, uncovered a wide range of methods, implications, applications, concerns, requirements, challenges, models, tools, datasets, and modalities related to deepfakes. Finally, a discussion on recommendations for policymakers, researchers, and other stakeholders is also provided.

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Keywords

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