Vol. 20 / 2025 – International Conference on Virtual Learning


Bibliometric analysis of ChatGPT based on Scopus data: Global research trends (2022-2024)

Kevin MEJÍA RIVERA, Mirna RIVERA GARCÍA, Luis REYES FLORES

Abstract:

The emergence of ChatGPT has reshaped academia and research, generating both enthusiasm and concerns. While ethical challenges persist, a growing movement advocates for its integration and the adoption of best practices. Objective: This study conducts a bibliometric analysis of scientific publications on ChatGPT indexed in Scopus (2022–2024) to map trends and characterize the academic output related to this technology. Methods: A systematic bibliometric analysis was performed following the PRISMA protocol. Data were extracted from Scopus, identifying 437 relevant publications. A statistical analysis using VOSviewer enabled the identification of 13 clusters and 32 nodes. Results: The analysis revealed that the majority of publications originated from the United States (24.80%), India (11.17%), and China (11.17%). The predominant publication types were journal articles (45.3%) and conference papers (36.8%). The most active research fields include Computer Science (27.7%), Medicine (14.5%), and Social Sciences (13.2%). Conclusions: Findings underscore the increasing prominence of ChatGPT as an interdisciplinary research topic. Key areas of focus include: the evolution of language models, response accuracy, impact on education and healthcare, and challenges and opportunities that AI presents in academic research.

Keywords:
Scopus, ChatGPT, Bibliometric Analysis, Scientific Production

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CITE THIS PAPER AS:
Kevin MEJÍA RIVERA, Mirna RIVERA GARCÍA, Luis REYES FLORES, "Bibliometric analysis of ChatGPT based on Scopus data: Global research trends (2022-2024)", International Conference on Virtual Learning, ISSN 2971-9291, ISSN-L 1844-8933, vol. 20, pp. 267-278, 2025. https://doi.org/10.58503/icvl-v20y202522