Analyzing public sentiment during national healthcare system failures: A big data approach to emergency department experiences in South Korea - Lina Wen; SangYoon Lim (PLoS ONE, 2026)
Background The 2024 healthcare crisis in South Korea, characterized by a mass resignation of medical residents and a subsequent “medical void,” has profoundly disrupted the healthcare landscape. This study aims to investigate the emotional responses and behavioral concerns of patients regarding emergency departments (EDs) during this period of systemic instability. Methods Utilizing AI-based text mining and sentiment analysis, we analyzed a comprehensive dataset of 1,359,146 unstructured data points harvested from major Korean online platforms between January 1, 2024, and December 31, 2024. The analysis focused on quantifying sentiment polarity and identifying core thematic stressors through keyword frequency and association mapping. Results The findings revealed a predominant negative sentiment (45.8%), significantly outweighing positive (32.4%) and neutral (21.9%) responses. Beyond clinical outcomes, specific terms such as “Medical Void,” “Emergency Room Runarounds,” and “Overtreatment” emerged as primary psychological stressors. Temporal and spatial analyses indicated that dissatisfaction spiked during holidays and nighttime, particularly concentrated in metropolitan areas like Seoul, reflecting critical bottlenecks in the emergency care network. Conclusions These results suggest that patient dissatisfaction during a national medical crisis transcends service-level issues, reflecting a deep-seated trust deficit and a perceived threat to psychological safety. This study provides a foundational evidence base for developing data-driven crisis communication systems and policy interventions aimed at restoring public trust and enhancing healthcare system resilience during national emergencies.