This study aims to enhance urban community resilience from the perspective of social networks in mitigating disaster impacts. It addresses the critical gap in systematic quantifying resilience, with a particular focus on stakeholder interactions within urban communities.
The study proposes an integrated framework leveraging social network analysis (SNA) to map stakeholder interactions across three distinct phases. Network metrics are employed as evaluation indicators, while a hybrid evaluation model combining the coefficient of variation (COV) and the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is utilized to quantify resilience levels of urban communities.
Applying the framework to Community F in Xuzhou City revealed significant variations in social networks during the three phases, with the disaster response phase demonstrating the most intense interactions. Furthermore, the resilience levels exhibited a consistent downward trend across three phases.
This research provides a novel approach to disaster management and resilience by integrating SNA with hybrid evaluation models. It advances theoretical insights and provides practical strategies for enhancing urban community resilience, contributing to the reduction of urban vulnerabilities to disasters.
