To investigate publication trends and research topics related to generative artificial intelligence in higher education, this study analyzes 141 articles published between 2019 and 2023, retrieved from the Web of Science database. Using bibliometric analysis and the bibliometrix package in R programming, the study examines the current state of research on generative artificial intelligence applications in higher education. The analysis provides insights into publication trends, most cited references and countries, popular keywords, and thematic maps in the field. Key findings reveal that research publication trends in this domain had no significant growth from 2019 to 2022 but saw a rapid increase in 2023, with a compound annual growth rate of 176.56%, indicating that this field has been flourishing in recent years. The top five popular keywords are “ChatGPT” (generative pre-trained transformer), “large language model,” “academic integrity,” “chatbot,” and “assessment.” Current research domains that are significant and well developed are grouped into three clusters of motor themes: the first cluster includes “ChatGPT,” “large language model,” and “academic integrity”; the second cluster features “digital humanities,” “digital,” and “literacy”; the third cluster focuses on “learning,” “critical thinking,” and “teacher education.” Areas identified as important but underdeveloped in basic and transversal themes include clusters related to “generative adversarial networks,” “deep learning,” and “quality.”