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

Faiza Farhat, Emmanuel Sirimal Silva, Hossein Hassani, Dag Øivind Madsen*, Shahab Saquib Sohail, Yassine Himeur, M. Afshar Alam, Aasim Zafar

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

8 Citations (Scopus)
21 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number1270749
Number of pages18
JournalFrontiers in Artificial Intelligence
Volume6
DOIs
Publication statusPublished - 5 Jan 2024

Keywords

  • application domains
  • bibliometric analysis
  • ChatGPT
  • citation analysis
  • collaborative networks
  • future directions
  • research trends
  • scientometric methods

ASJC Scopus subject areas

  • Artificial Intelligence

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