Unmasking the Digital Illusion: A Comprehensive Bibliometric Analysis of Deepfake Detection Research

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Abstract

This study conducts an in-depth bibliometric review of research on deepfake detection spanning from 2019 to 2024, identifying key advancements and patterns within this essential field. Utilizing sophisticated data scraping and analysis methods, we examined a wide range of scholarly articles gathered from leading databases, emphasizing trends in publication frequency, citation impact, and thematic shifts. The results indicate a significant rise in research activities, with notable contributions primarily originating from China, as well as extensive international collaborations, especially between Chinese and American researchers.

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Keywords

Bibliometric Analysis; Deepfake detection; Generative Adversarial network (GAN)