Virtual vitality has become an important complementary dimension for describing urban vitality; however, the identification and formation mechanisms of its stable, high-vitality state during dynamic change remain insufficiently explored. Taking five urban districts of Harbin as the study area, this study uses TikTok short-video data from July to August 2024 (summer) and December 2024 to January 2025 (winter), together with Gaode Map POI data, as the core dataset. Kernel density differences between adjacent weeks are used to measure the dynamic changes in virtual vitality. Bivariate local spatial autocorrelation is applied to identify high-vitality stable zones, and a Random Forest model is employed to examine the nonlinear influence of physical vitality spatial structures. The results show the following: (1) Dynamic change patterns of virtual vitality differ significantly across seasons, and when online attention content points to specific physical spatial structures, a stable high-vitality state is more likely to be maintained. (2) Bivariate local spatial autocorrelation analysis indicates that high-vitality stable zones (HH zones) exhibit significant spatial clustering, with vitality-enhancing zones (LH zones) distributed around them and showing spillover effects, while vitality-declining zones (HL zones) are more scattered. (3) The Random Forest results show that the stable maintenance of high virtual vitality depends more on combinations of spatial structural characteristics with high recognizability, among which distance to activity center (tourism), functional composition dissimilarity (culture), and functional composition dissimilarity (shopping) have the strongest influence. These findings reveal a nonlinear relationship between the stable high-vitality state and the structure of physical vitality space, providing insights for guiding online attention to support physical spatial development.
Gong et al. (Thu,) studied this question.