Mapping the intersection of artificial intelligence and neuroticism: a bibliometric analysis

The intersection of artificial intelligence (AI) and neuroticism has gained increasing scholarly attention, influencing domains such as mental health, human–computer interaction, and AI-driven behavioural analysis. Despite growing research, there is limited synthesis of trends, influential contributors, and emerging themes in this field. This study aims to provide a comprehensive bibliometric overview of AI applications in neuroticism research. The study draws on personality psychology and bibliometric theory to map the intellectual landscape. Concepts such as trait neuroticism, AI-driven behavioural modelling, and thematic clustering underpin the analysis. Bibliometric approaches – including co-citation, bibliographic coupling, and keyword co-occurrence – provide the framework to examine research development and collaboration patterns. A systematic bibliometric analysis was conducted on 321 Scopus-indexed articles. Data were analysed using co-occurrence of keywords, co-citation analysis, thematic clustering, and bibliographic coupling. The study identified key authors, institutions, journals, citation patterns, and thematic clusters, covering research from 2015 to 2025. Eight major thematic clusters were identified, including AI-driven personality assessment, social media behaviour, trust in AI, and emotion recognition. The USA and China emerged as the most prolific contributors, with the University of Pennsylvania leading in institutional productivity. Computers in Human Behaviour and Frontiers in Psychology were the most influential journals. The findings highlight gaps in AI-driven psychological interventions, ethical considerations, and cross-cultural studies. Future research should focus on deep learning techniques for personality modelling, human–AI trust dynamics, and integrating AI into psychological assessments. This bibliometric mapping provides a roadmap to guide interdisciplinary research at the intersection of AI and personality psychology.

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Publication Details

Journal
Critical Public Health
Published
2025-12-13
DOI
https://doi.org/10.1080/09581596.2025.2598715
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
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Mapping the intersection of artificial intelligence and neuroticism: a bibliometric analysis

Critical Public Health
Personality Traits and Psychology
article

Mapping the intersection of artificial intelligence and neuroticism: a bibliometric analysis

article en

Abstract

The intersection of artificial intelligence (AI) and neuroticism has gained increasing scholarly attention, influencing domains such as mental health, human–computer interaction, and AI-driven behavioural analysis. Despite growing research, there is limited synthesis of trends, influential contributors, and emerging themes in this field. This study aims to provide a comprehensive bibliometric overview of AI applications in neuroticism research. The study draws on personality psychology and bibliometric theory to map the intellectual landscape. Concepts such as trait neuroticism, AI-driven behavioural modelling, and thematic clustering underpin the analysis. Bibliometric approaches – including co-citation, bibliographic coupling, and keyword co-occurrence – provide the framework to examine research development and collaboration patterns. A systematic bibliometric analysis was conducted on 321 Scopus-indexed articles. Data were analysed using co-occurrence of keywords, co-citation analysis, thematic clustering, and bibliographic coupling. The study identified key authors, institutions, journals, citation patterns, and thematic clusters, covering research from 2015 to 2025. Eight major thematic clusters were identified, including AI-driven personality assessment, social media behaviour, trust in AI, and emotion recognition. The USA and China emerged as the most prolific contributors, with the University of Pennsylvania leading in institutional productivity. Computers in Human Behaviour and Frontiers in Psychology were the most influential journals. The findings highlight gaps in AI-driven psychological interventions, ethical considerations, and cross-cultural studies. Future research should focus on deep learning techniques for personality modelling, human–AI trust dynamics, and integrating AI into psychological assessments. This bibliometric mapping provides a roadmap to guide interdisciplinary research at the intersection of AI and personality psychology.

Critical Public HealthVol. 36(1)
Binus University (ID), University of Brawijaya (ID), Rockford University (US), Shree Guru Gobind Singh Tricentenary University (IN), Stanford Medicine (US)
Decent work and economic growth
Openalex Percentile: Top 30%
Personality Traits and Psychology
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