The Relationship between Emotional Perception and High-Density Built Environment Based on Social Media Data: Evidence from Spatial Analyses in Wuhan

Abstract

The utilization of Social Media Data (SMD) from location-based services offers a wealth of information to analyze changes in human emotional perception influenced by high-density built environments. This study aimed to examine the impact of high-density built environment factors on human emotion perception. First, a set of indicators for high-density built environments was established. Subsequently, Natural Language Processing (NLP) was employed to analyze SMD for sentiment identification and classification. Finally, the Multi-scale Geographically Weighted Regression (MGWR) model was utilized to investigate the spatial differentiation of human emotional perception in high-density built environments. The findings revealed that positive emotions display spatial variations in high-density built environments. Additionally, positive emotions were found to be influenced by multiple variables, with different variables simultaneously affecting individuals’ positive emotions. Specific built environment indicators showed positive correlations with Open Space Ratio (OSR), Green Space Ratio (GSR), POI Functional Density (PFD), and Road Network Density (RND), while negative correlations with Floor Space Index (FSI), Ground Space Index (GSI), Building Average Layer (BAL), Water Index (WI), and Space Syntax Integration (SSI) were observed. Normalized Difference Vegetation Index (NDVI), POI Functional Mixture (PFM), Space Syntax Choice (SSC), and Population Density (PD) exhibited mixed results in different spatial contexts. This research on human perception provides insights for refined urban design and governance, addressing the limitations of top-down approaches in dense urban renewal.