Mapping the Landscape of AI-empowered Psychology: A Topic Modeling-based Bibliometric Analysis

The integration of artificial intelligence (AI) is profoundly reshaping psychological research and practice, creating a dynamic and complex landscape. This study systematically maps the field of "AI-empowered psychology" to understand its thematic structure, developmental trajectory, and publication patterns. We conducted a bibliometric and BERTopic-based topic modeling analysis of 10,079 peer-reviewed articles (2000–2024) from the Web of Science. The analysis identified 27 distinct research topics clustered into seven major domains: Cognitive Modeling, AI-powered Psychometrics, Computational Psychiatry, BCI Study and Applications, AI-augmented Learning Science, Human-AI Interaction, and Digital Mental Health Intervention. These domains exemplify the profound integration of AI within psychology, showcasing its dual function: as a powerful tool to advance the scientific goals of description, explanation, prediction, and control, and as a novel research object in its own right. Temporal analysis revealed a three-phase evolution, propelled by technological breakthroughs such as deep learning and large language models (LLMs). Publication analysis highlighted key international research hubs and collaboration networks, while also revealing potential data diversity challenges. This comprehensive mapping provides a valuable framework for researchers to navigate the evolving field of AI-empowered psychology, illuminating current frontiers, developmental trends, and critical considerations for future research and application.