ISSN : 1229-2435
This study conducted a bibliometric analysis based on keyword network analysis to identify research trends on generative AI in the field of library and information science. After collecting articles on the topic of “generative AI” from the Web of Science database, word frequency analysis and TF-IDF analysis were performed. Centrality measures were also applied to extract key keywords. In addition, the CONCOR algorithm, based on the concept of structural equivalence, was used to create blocks with similar semantic structures, and the thematic characteristics of each block were analyzed. The results of the analysis are as follows: First, the application and education of generative AI were found to be the most commonly used and influential subject areas in the field of library and information science. Second, The research was shown to be expanding into areas such as response generation using RAG technology applied to GPT, decision support systems, and convergence with domains such as education and healthcare.