Human Interaction with Generative AI in Higher Education Research: A Bibliometric Analysis of the Humanities and Social Sciences (2015–2025)

This bibliometric analysis seeks to create a picture of the intellectual and structural paradigm of creative artificial intelligence research in the humanities and social sciences from 2015 to 2025. This analysis of 1,234 Scopus-indexed documents employs performance metrics, science mapping, and logistic growth modelling employing VOSviewer and Bibliometrix software to examine the publication dynamics, geography, and institutional distribution, journal networks, authorship, and themes. The results show that the publication dynamics follow an exponential growth pattern with a 34.37% annual growth rate and are dominated by authors from the US, the UK, and China. The authorship analysis indicates a fragmented landscape dominated by a few seminal works. Five major themes have emerged computational methods, GenAI tools, ethics, human-centred research, and sustainability. Educational journals have the highest citation impact. This analysis provides a framework for comprehending the human GenAI interaction in higher education settings by structuring the field and defining its research fronts, thereby answering the underexplored aspects of effective human GenAI interaction, trade-offs in educational results, and evidence-based design that have emerged as key issues in recent scholarly agendas.