Bibliometric Analysis of Generative AI and Large Language Models in the Scopus Database: Trends, Insights, and Research Landscape

Abstract

This bibliometric study explores the scientific research landscape by analyzing journal sources, author productivity, institutional contributions, and national research output using bibliometric laws such as Bradford’s Law and Lotka’s Law. The findings identify IEEE ACCESS as the most influential journal, with 26 articles, dominating Zone 1 publications. Lotka’s Law is validated as 94% of authors contributed only one article, while a small group of researchers produced multiple influential works. Institutional analysis shows that the University of California, Cornell University, and Nanyang Technological University significantly increased their research output over time. At the national level, the USA leads with 238 publications, followed by China (77), India (69), and the UK (61). While these results highlight the major contributors to the field, the study also discusses challenges such as data limitations, citation lag effects, and geographical concentration of research efforts. This analysis provides a comprehensive overview of current trends, aiding researchers and policymakers in understanding the dynamics of scientific productivity and influence.

Ähnliche Arbeiten