TY - JOUR
T1 - The Distinctive Social Emotion Network and Process Following Natech Accidents
T2 - Evidence From China
AU - Yan, Xiaohan
AU - Wu, Chen
AU - Liu, Yi
AU - Liu, Tiezhong
N1 - Publisher Copyright:
© 2025 John Wiley & Sons Ltd.
PY - 2025/6
Y1 - 2025/6
N2 - The frequency and risk of Natech (Natural Hazard Triggered Technological) accidents have risen significantly within the context of increased extreme weather events and accelerated global industrialisation. As disasters that combine unpredictability and complexity, Natech accidents tend to generate and accumulate negative emotions in patterns that differ markedly from other types of incidents, making it crucial to study the characteristics of social emotion generation and interaction to better manage public emotions in Natech accidents. This study conducts a case study of “Beijing Subway Changping Line Accident” and applies the Social Network Analysis (SNA) method to examine how network structure, key nodes, and network positions influence the generation pathway and the intensity of social emotion across the stages of this Natech accident. The results reveal that social emotions in Natech accidents exhibit a negative inclination, stronger than those in natural disasters, but weaker than those in technological accidents. The interplay of natural disasters and technological accidents triggers a rapid escalation of social emotions in Natech accidents. In emergency management of Natech accidents, the government plays a leading role, while NGOs and media serve as auxiliary forces, collectively facilitating the interpretation and communication of accidents to de-escalate public attention and guide emotional trajectories. The negative emotions stem mainly from the specific nature of the accident rather than from purely natural or technological causes. This study is among the earliest explorations of the mechanisms behind social emotion generation in Natech accidents based on Chinese cases. It constructs a customised emotion dictionary for the accident and enriches the indicators for measuring emotions. It reveals the social emotion trends from a social network structure perspective, which provides nuanced insights into the effective management of public emotions in Natech accidents.
AB - The frequency and risk of Natech (Natural Hazard Triggered Technological) accidents have risen significantly within the context of increased extreme weather events and accelerated global industrialisation. As disasters that combine unpredictability and complexity, Natech accidents tend to generate and accumulate negative emotions in patterns that differ markedly from other types of incidents, making it crucial to study the characteristics of social emotion generation and interaction to better manage public emotions in Natech accidents. This study conducts a case study of “Beijing Subway Changping Line Accident” and applies the Social Network Analysis (SNA) method to examine how network structure, key nodes, and network positions influence the generation pathway and the intensity of social emotion across the stages of this Natech accident. The results reveal that social emotions in Natech accidents exhibit a negative inclination, stronger than those in natural disasters, but weaker than those in technological accidents. The interplay of natural disasters and technological accidents triggers a rapid escalation of social emotions in Natech accidents. In emergency management of Natech accidents, the government plays a leading role, while NGOs and media serve as auxiliary forces, collectively facilitating the interpretation and communication of accidents to de-escalate public attention and guide emotional trajectories. The negative emotions stem mainly from the specific nature of the accident rather than from purely natural or technological causes. This study is among the earliest explorations of the mechanisms behind social emotion generation in Natech accidents based on Chinese cases. It constructs a customised emotion dictionary for the accident and enriches the indicators for measuring emotions. It reveals the social emotion trends from a social network structure perspective, which provides nuanced insights into the effective management of public emotions in Natech accidents.
UR - http://www.scopus.com/inward/record.url?scp=105007613317&partnerID=8YFLogxK
U2 - 10.1111/1468-5973.70060
DO - 10.1111/1468-5973.70060
M3 - Article
AN - SCOPUS:105007613317
SN - 0966-0879
VL - 33
JO - Journal of Contingencies and Crisis Management
JF - Journal of Contingencies and Crisis Management
IS - 2
M1 - e70060
ER -