The scholarly footprint of ChatGPT: a bibliometric analysis of the early outbreak phase

被引:16
作者
Farhat, Faiza [1 ]
Silva, Emmanuel Sirimal [2 ]
Hassani, Hossein [3 ]
Madsen, Dag oivind [4 ]
Sohail, Shahab Saquib [5 ]
Himeur, Yassine [6 ]
Alam, M. Afshar [5 ]
Zafar, Aasim [7 ]
机构
[1] Aligarh Muslim Univ, Dept Zool, Aligarh, India
[2] Glasgow Caledonian Univ, Glasgow Sch Business & Soc, Dept Econ & Law, Glasgow City, Scotland
[3] Univ Tehran, Res Inst Energy Management & Planning RIEMP, Tehran, Iran
[4] Univ South Eastern Norway, USN Sch Business, Honefoss, Norway
[5] Jamia Hamdard, Sch Engn Sci & Technol, Dept Comp Sci & Engn, New Delhi, India
[6] Univ Dubai, Coll Engn & Informat Technol, Dubai, U Arab Emirates
[7] Aligarh Muslim Univ, Dept Comp Sci, Aligarh, India
来源
FRONTIERS IN ARTIFICIAL INTELLIGENCE | 2024年 / 6卷
基金
英国科研创新办公室;
关键词
ChatGPT; bibliometric analysis; scientometric methods; research trends; citation analysis; collaborative networks; application domains; future directions;
D O I
10.3389/frai.2023.1270749
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a comprehensive analysis of the scholarly footprint of ChatGPT, an AI language model, using bibliometric and scientometric methods. The study zooms in on the early outbreak phase from when ChatGPT was launched in November 2022 to early June 2023. It aims to understand the evolution of research output, citation patterns, collaborative networks, application domains, and future research directions related to ChatGPT. By retrieving data from the Scopus database, 533 relevant articles were identified for analysis. The findings reveal the prominent publication venues, influential authors, and countries contributing to ChatGPT research. Collaborative networks among researchers and institutions are visualized, highlighting patterns of co-authorship. The application domains of ChatGPT, such as customer support and content generation, are examined. Moreover, the study identifies emerging keywords and potential research areas for future exploration. The methodology employed includes data extraction, bibliometric analysis using various indicators, and visualization techniques such as Sankey diagrams. The analysis provides valuable insights into ChatGPT's early footprint in academia and offers researchers guidance for further advancements. This study stimulates discussions, collaborations, and innovations to enhance ChatGPT's capabilities and impact across domains.
引用
收藏
页数:18
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