An emotion-behavior perspective of understanding public and government responses to rainstorm disasters: A case study of Zhengzhou Rainstorm in China

Abstract

Understanding public emotional and behavioral response is critical for adaptive disaster management. Integrating natural language processing (NLP), econometric, and social psychological models, this study establishes an emotion-behavior framework to analyze multidimensional interactions between public and government responses. Using social media data from “7.20” Zhengzhou Rainstorm, we reveal distinct emotional drivers: social support offering (SSO) thrived on positive emotions, yet help seeking (HSK) correlated with fear, deviance (DEV) driven by anger, and avoidance & venting (A&V) sustained by multiple negative emotions. Public behavior patterns shifted from pre-disaster instrumental aid to fear-driven avoidance coupled with emotional aid arising during crises, eventually evolving into intensified post-disaster resource competition. Government strategies show asymmetric impacts on these behaviors. Most strategies yielded instantly positive effects on SSO, while all strategies responded passively to HSK and some had time-lag or limited effects in mitigating A&V and DEV. The findings advocate integrating psychosocial factors into emergency strategies, with emphases on prioritizing proactive community engagement to sustain social cohesion, embedding psychological support mechanisms, and enforcing transparent resource governance to redirect emotions like fear, anger, and sadness. This approach advances urban resilience by highlighting that adaptive climate defenses requires aligning policy interventions with community-driven collaboration and emotion-driven public behavioral dynamics.