Users’ Emotional Diffusion and Public Opinion Evolution Under Public Health Emergencies: Taking the Community Group Purchasing on Zhihu as an Example

COVID-19 closures forced community residents to organize daily supply group purchasing for anti-epidemic needs. Public service satisfaction constitutes an important public health emergency governance indicator. Analyzing community group purchasing satisfaction emotional diffusion assists governments in timely, comprehensively grasping mass needs, resolving main public opinion development contradictions across stages, and maintaining stability amid special periods. User comment text spanning December 19, 2019 to August 2, 2021 was captured for five related Zhihu community topics. After cleaning, 2,034 items were utilized to calculate user emotional tendency scores. Ebbinghaus forgetting curves were then introduced for interpolation fitting to form complete community purchasing satisfaction time series. Regional influence on time series patterns was studied using three city Zhihu data. Autoregressive integrated moving average (ARIMA) models constructed with Wuhan and Shijiazhuang outbreak phase data predicted public opinion evolution regarding community purchasing satisfactio. Wuhan demonstrated “flat before, medium, tight and slow” characteristics. Shijiazhuang exhibited “low middle and high sides”. Guangzhou showed cyclical “steady-decreasing-rising” tendencies. Emotions gradually became cyclical and smooth. The research examines real-time public community group purchasing needs amid public health emergencies like epidemics from the public stance. Analyzing digital traces of public sentiments during crises provides data-driven insights to guide responsive governance. Further research should expand datasets across platforms and issues while refining techniques to extract signals from noise. Findings can illuminate universal public opinion dynamics to better predict future trajectories. Integrating computational social science, data science and psychology can strengthen collective resilience.