Abstract
Following the initial COVID-19 pandemic in China, major cities faced the critical task of balancing pandemic prevention and control with economic recovery. This study explores how each local government allocates its attention resources by analyzing textual information related to COVID-19 in the official websites of Beijing, Dalian, Qingdao, and Shanghai. Using Structural Topic Modeling (STM) and Social Network Analysis (SNA), we identified the main features of textual topics, the relationships between topics, the trends over time, and how the topics changed across document types. Our analysis showed that local governments set priorities based on their administrative autonomy and the severity of the epidemic. Therefore, resilience building in cities against epidemics should consider both factors and adopt differentiated strategies and multilevel approaches.
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