Generative AI in Academic Publishing: A Bibliometric Analysis and Emerging Debates on Integrity, Authorship, and Language Equity

Abstract

The rapid development of generative artificial intelligence (AI) tools, particularly large language models such as ChatGPT, has generated significant debate within the academic publishing community. This study examines emerging research trends and discussions surrounding the use of generative AI in scientific writing and publishing. Using a bibliometric approach, the study analyses 311 documents indexed in the Scopus database and published between 2023 and 2025. The dataset was processed using the Bibliometrix R package to identify publication trends, frequently used keywords, and thematic relationships. Visualisation techniques, including a word cloud and a keyword co-occurrence network, were employed to map the conceptual structure of the field. The analysis reveals three primary thematic clusters: a technological cluster focused on AI tools and scientific writing, a biomedical-ethical cluster addressing clinical and educational implications, and a publishing-integrity cluster concerned with research ethics, authorship, plagiarism, and peer review. The findings indicate that debates about generative AI in academic publishing are strongly connected to issues of transparency, accountability, and the reliability of scholarly communication. The study highlights the importance of clear editorial policies, responsible AI use, and disclosure practices to maintain research integrity while supporting accessibility and linguistic equity in academic publishing.