Dynamic Evolution of Government–Society Collaborative Networks in Earthquake Emergency Response: A Case Study of the 2025 Dingri Earthquake

Objective: To explore the dynamic evolution and underlying mechanisms of government–society collaborative networks across stages of earthquake emergency response in a high-altitude region. Methods: Using the 2025 magnitude 6.8 Dingri earthquake in Xizang, China, as a case, this study constructed a two-mode actor–activity network and a one-mode actor–actor network using publicly available data. Government–society collaboration during the emergency rescue stage and the affected-population resettlement stage was compared across in terms of collaboration structure, process, and role. Results: The emergency rescue stage exhibited a relatively centralized network structure dominated by core government actors. During resettlement, the government–society network shifted to polycentric collaboration under unified government coordination, with higher network density, shorter path lengths, and lower centralization. As tasks expanded from force mobilization and lifesaving rescue to resettlement, material support, and livelihood services, government actors shifted from internal mobilization to inclusive coordination, while societal actors transitioned from dispersed participation to organized collaboration. Grassroots organizations and societal actors with local linguistic and cultural knowledge served as bridging actors in demand reporting, resource coordination, and last-mile service delivery. Conclusion: Government–society collaboration in the Dingri earthquake involved not simply a numerical increase in societal actors, but a process through which evolving emergency tasks drove a collective realignment of interorganizational relationships, collaborative modes, and actor roles. These findings inform the development of institutionalized coordination mechanisms for societal actors, clearer task allocation during disasters, and stronger grassroots emergency-service capacity in high-altitude ethnic minority areas.