Artículo

Bibliometric Analysis on ChatGPT Research with CiteSpace

Resumen

ChatGPT is a generative artificial intelligence (AI) based chatbot developed by OpenAI and has attracted great attention since its launch in late 2022. This study aims to provide an overview of ChatGPT research through a CiteSpace-based bibliometric analysis. We collected 2465 published articles related to ChatGPT from the Web of Science. The main forces in ChatGPT research were identified by examining productive researchers, institutions, and countries/regions. Moreover, we performed co-authorship network analysis at the levels of author and country/region. Additionally, we conducted a co-citation analysis to identify impactful researchers, journals/sources, and literature in the ChatGPT field and performed a cluster analysis to identify the primary themes in this field. The key findings of this study are as follows. First, we found that the most productive researcher, institution, and country in ChatGPT research are Ishith Seth/Himel Mondal, Stanford University, and the United States, respectively. Second, highly cited researchers in this field are Tiffany H. Kung, Tom Brown, and Malik Sallam. Third, impactable sources/journals in this area are ARXIV, Nature, and Cureus Journal of Medical Science. Fourth, the most impactful work was published by Kung et al., who demonstrated that ChatGPT can potentially support medical education. Fifth, the overall author-based collaboration network consists of several isolated sub-networks, which indicates that the authors work in small groups and lack communication. Sixth, United Kingdom, India, and Spain had a high degree of betweenness centrality, which means that they play significant roles in the country/region-based collaboration network. Seventh, the major themes in the ChatGPT area were “data processing using ChatGPT”, “exploring user behavioral intention of ChatGPT”, and “applying ChatGPT for differential diagnosis”. Overall, we believe that our findings will help scholars and stakeholders understand the academic development of ChatGPT.
Nan, Dongyan (57216459705); Zhao, Xiangying (57469526300); Chen, Chaomei (7501950297); Sun, Seungjong (57560510900); Lee, Kyeo Re (57219228965); Kim, Jang Hyun (35334398800)
Bibliometric Analysis on ChatGPT Research with CiteSpace
2025
10.3390/info16010038
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215756178&doi=10.3390%2finfo16010038&partnerID=40&md5=f05459b8b2862d6d838ae47c835bd923
School of Business, Macau University of Science and Technology, 999078, Macao; Department of Interaction Science, Sungkyunkwan University, Seoul, 03063, South Korea; College of Computing and Informatics, Drexel University, Philadelphia, 19104, PA, United States; Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, 03063, South Korea; Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, 03063, South Korea; Center for Creative Convergence Education, Hanyang University ERICA, Ansan, 15588, South Korea
All Open Access; Gold Open Access
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