Autonomous driving paper index
Mapping the landscape of psychological literature on threat from 1961 to 2023 through structural topic modeling
One-line summary
The past decades have generated a substantial volume of psychological literature on threat.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
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Original abstract
The past decades have generated a substantial volume of psychological literature on threat. However, the absence of systematic cross-field synthesis has resulted in limited understanding of major research domains and relationships between different lines of threat research. We analyzed 51,903 psychological publications on threat retrieved from APA PsycInfo, Scopus, and Web of Science Core Collection that were published between 1961 and 2023. We conducted structural topic modeling on publication titles and abstracts to identify key research topics, and network analysis on the resulting topics to map the thematic structure of the literature. 25 topics emerged, organized into four thematic areas through exploratory graph analysis: 1) threat processing mechanisms, 2) health and clinical threats, 3) social psychological threats, and 4) collective threats. Network analysis revealed differential connectivity patterns within and between thematic areas. Areas showed limited connectivity with each other and no area emerged as a central hub, suggesting gaps in cross-domain integration. Topic prevalence trends revealed diversification in research interest over time, together with responsiveness to broader developments within psychology and evolving societal concerns. Notably, mechanism-focused research declined over the past decade while event-driven research on specific threats increased, indicating reactive rather than theory-driven investigation. These findings provide insights into the landscape of psychological literature on threat and reveal critical gaps in current examinations alongside strategic opportunities to advance cross-field integration.
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