Developing a Real-Time Public Opinion Analysis System for Women’s Reemployment in Taiwan: A Digital Transformation Approach to Policy Innovation

Abstract

Declining fertility and population aging intensify labor shortages, making women’s reemployment after caregiving a policy priority. Using Taiwan as a case study, this study develops a real-time public opinion analysis system to complement delayed surveys and capture emerging barriers in labor-market reintegration. Drawing on 2022–2024 social media posts, the system applies sentiment co.mputing, clustering, and algorithmic attention to map four phases: withdrawal, intention, search, and reintegration. Findings show that younger women stress flexibility and childcare, while older returnees prioritize skill renewal and confidence rebuilding; sectoral variation supports life-cycle and clockspeed theories. Policy recommendations emphasize subsidies, training, quotas, and street-level implementation. Beyond technical contributions, the study embeds digital transformation (DT) into labor governance, showing a shift from as-is retrospective surveys to to-be-real-time monitoring. This transformation enhances policy agility, inclusiveness, and alignment with citizens’ lived experiences. The system thus functions as both a tool for rapid intervention and a DT-driven theoretical lens extending reemployment scholarship, offering transferable insights for aging societies.