Your browser doesn't support javascript.
loading
The scholarly footprint of ChatGPT: a bibliometric analysis of the early outbreak phase.
Farhat, Faiza; Silva, Emmanuel Sirimal; Hassani, Hossein; Madsen, Dag Øivind; Sohail, Shahab Saquib; Himeur, Yassine; Alam, M Afshar; Zafar, Aasim.
Afiliación
  • Farhat F; Department of Zoology, Aligarh Muslim University, Aligarh, India.
  • Silva ES; Department of Economics and Law, Glasgow School for Business and Society, Glasgow Caledonian University, Glasgow, United Kingdom.
  • Hassani H; The Research Institute of Energy Management and Planning (RIEMP), University of Tehran, Tehran, Iran.
  • Madsen DØ; USN School of Business, University of South-Eastern Norway, Hønefoss, Norway.
  • Sohail SS; Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.
  • Himeur Y; College of Engineering and Information Technology, University of Dubai, Dubai, United Arab Emirates.
  • Alam MA; Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.
  • Zafar A; Department of Computer Science, Aligarh Muslim University, Aligarh, India.
Front Artif Intell ; 6: 1270749, 2023.
Article en En | MEDLINE | ID: mdl-38249789
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.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Front Artif Intell Año: 2023 Tipo del documento: Article País de afiliación: India Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Systematic_reviews Idioma: En Revista: Front Artif Intell Año: 2023 Tipo del documento: Article País de afiliación: India Pais de publicación: Suiza