Global insights and the impact of generative AI-ChatGPT on multidisciplinary: a systematic review and bibliometric analysis

Khan, Nauman and Khan, Zahid and Koubaa, Anis and Khan, Muhammad Khurram and Salleh, Rosli (2024) Global insights and the impact of generative AI-ChatGPT on multidisciplinary: a systematic review and bibliometric analysis. Connection Science, 36 (1). p. 2353630. ISSN 0954-0091, DOI https://doi.org/10.1080/09540091.2024.2353630.

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Official URL: https://doi.org/10.1080/09540091.2024.2353630

Abstract

In 2022, OpenAI's unveiling of generative AI Large Language Models (LLMs)- ChatGPT, heralded a significant leap forward in human-machine interaction through cutting-edge AI technologies. With its surging popularity, scholars across various fields have begun to delve into the myriad applications of ChatGPT. While existing literature reviews on LLMs like ChatGPT are available, there is a notable absence of systematic literature reviews (SLRs) and bibliometric analyses assessing the research's multidisciplinary and geographical breadth. This study aims to bridge this gap by synthesising and evaluating how ChatGPT has been integrated into diverse research areas, focussing on its scope and the geographical distribution of studies. Through a systematic review of scholarly articles, we chart the global utilisation of ChatGPT across various scientific domains, exploring its contribution to advancing research paradigms and its adoption trends among different disciplines. Our findings reveal a widespread endorsement of ChatGPT across multiple fields, with significant implementations in healthcare (38.6%), computer science/IT (18.6%), and education/research (17.3%). Moreover, our demographic analysis underscores ChatGPT's global reach and accessibility, indicating participation from 80 unique countries in ChatGPT-related research, with the most frequent countries keyword occurrence, USA (719), China (181), and India (157) leading in contributions. Additionally, our study highlights the leading roles of institutions such as King Saud University, the All India Institute of Medical Sciences, and Taipei Medical University in pioneering ChatGPT research in our dataset. This research not only sheds light on the vast opportunities and challenges posed by ChatGPT in scholarly pursuits but also acts as a pivotal resource for future inquiries. It emphasises that the generative AI (LLM) role is revolutionising every field. The insights provided in this paper are particularly valuable for academics, researchers, and practitioners across various disciplines, as well as policymakers looking to grasp the extensive reach and impact of generative AI technologies like ChatGPT in the global research community.

Item Type: Article
Funders: Prince Sultan University, King Saud University
Uncontrolled Keywords: LLM-ChatGPT; bibliometric analysis; interdisciplinary research; demographic analysis; generative AI; geographic distribution; 0000; 1111
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 17 Sep 2024 00:40
Last Modified: 17 Sep 2024 00:40
URI: http://eprints.um.edu.my/id/eprint/45082

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