This study presents a comprehensive approach that addresses the challenges of
scientometric analysis in the rapidly evolving field of Artificial Intelligence
(AI). By combining search terms related to AI with the advanced language
processing capabilities of generative pre-trained transformers (GPT), we
developed a highly accurate method for identifying and analyzing AI-related
articles in the Web of Science (WoS) database. Our multi-step approach included
filtering articles based on WoS citation topics, category, keyword screening,
and GPT classification. We evaluated the effectiveness of our method through
precision and recall calculations, finding that our combined approach captured
around 94% of AI-related articles in the entire WoS corpus with a precision of
90%. Following this, we analyzed the publication volume trends, revealing a
continuous growth pattern from 2013 to 2022 and an increasing degree of
interdisciplinarity. We conducted citation analysis on the top countries and
institutions and identified common research themes using keyword analysis and
GPT. This study demonstrates the potential of our approach to facilitate
accurate scientometric analysis, by providing insights into the growth,
interdisciplinary nature, and key players in the field.Comment: 29 pages, 10 figures, 5 table