Mapping the Scientific Literature on the Metaverse and Artificial Intelligence in the Web of Science Database

Purpose: This study aimed to construct a knowledge map and analyze publications in the field of the Metaverse and Artificial Intelligence using data from the Web of Science (WoS) database. Method: This applied research adopts a scientometric approach. Data were extracted from WoS using the advanced search function with the keywords 'Metaverse' and 'Artificial Intelligence,' resulting in a dataset of 5,040 records. After cleaning and standardizing the data, analyses were performed using Pybibx in Python and Bibliometrix in R. Findings: The findings offer an overview of research on the Metaverse and Artificial Intelligence from 1992 to 2024, spanning 107 countries and 3,922 institutions. A total of 141,763 references are cited across 1,081 sources, with English being the predominant language. Collaboration is a key feature, reflected by an average collaboration index of 4.34 and 4,871 multi-authored documents. The average citations per document are 19.46, signaling significant research impact. Although there are 18,123 authors, the average number of documents per author is low (1.21), indicating that many authors contribute fewer works. Institutions, however, average 13.19 documents. Other findings indicate that a total of 5,040 records in this subject area are indexed in the WoS database. China leads in contributions.

Mapping the Scientific Literature on the Metaverse and Artificial Intelligence in the Web of Science Database Keywords:

Metaverse , Artificial Intelligence , Web of Science , Scientific Literature , Scientometric , Pybibx , Bibliometrix , Collaboration , Research Impact , WoS Database