Future responses to elderly driver accident risks in South Korea: weak signal detection through news text analysis for public safety policy

This study applies text mining to South Korean news data to identify weak signals related to elderly drivers and analyze their policy implications. A total of 2264 news articles published between January 2024 and March 2025 were collected, and keyword-based weak signals were identified. Word network analysis interpreted relationships between weak signals and co-occurring terms. The results revealed five signal categories—acceleration/brake/activation, free, black box, sidewalk, and system—corresponding to driving errors, incentive-based policies, accident documentation, pedestrian safety, and administrative structures. The findings highlight the need for technical measures to prevent pedal misapplication, mobility-related support for those ceasing to drive, recording devices for accident analysis, protection infrastructure against sidewalk intrusion, and conditional licensing and integrated management systems for elderly drivers. Recognizing elderly driver-related accidents as a structural risk, this study provides insights for traffic safety and criminal justice policy using a weak signal detection approach grounded in public discourse.