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 delineate its thematic structure, developmental trajectory, and publication patterns. We conducted a BERTopic-based bibliometric analysis of 9190 documents (2000–2025) from the Web of Science Core Collection. The analysis identified 24 distinct research topics clustered into eight domains: Human-AI Interaction, Cognitive Modeling, AI-assisted Applied Psychology, Physiological Signal Processing, Computational Personality and Social Psychology, Computational Psychiatry, Digital Mental Health Intervention, and Affective and Creative Computing. These domains exemplify the extensive 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 two-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 geographic 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.