"Visually Vibrant but Functionally Fragile": Traffic Carrying Capacity Crisis and Public Opinion Evolution Logic in Rural Revitalization Micro-Nodes

Abstract

With the continuous deepening of digital rural construction, algorithmic traffic has spawned numerous "visually vibrant but functionally fragile" rural micro-nodes, which exhibit prominent landscape symbolisms yet lack sufficient infrastructure and governance carrying capacity. These nodes are prone to online public opinion risks under the impact of instantaneous high traffic. Existing studies on rural public opinion mostly focus on textual semantic analysis while overlooking rigid physical spatial constraints, making it difficult to accurately characterize the risk evolution patterns of micro-nodes. To address this gap, this study integrates spatial knowledge graphs with deep learning methods to construct a Spatial Knowledge-enhanced Topological Evolution Model (SK-TEM), analyzing the public opinion evolution mechanism of rural micro-nodes under traffic surges. Selecting rural case studies with distinct carrying capacities, we integrate Geographic Information System (GIS) and social media opinion data to conduct comparative simulations. The results indicate that: (1) The public opinion of rural micro-nodes exhibits a double-peak topological pattern characterized by "aesthetic resonance followed by feedback collapse," where physical spatial carrying capacity serves as the core rigid element determining opinion trajectories. (2) Compared with traditional text-based semantic models,SK-TEM achieves an overall risk identification accuracy of 89.4% and a macro-average F1-score of 88.3%,demonstrating significant improvement in early-warning performance.This study clarifies the coupled "space-emotion" evolution logic of rural areas, breaks through the limitations of pure text opinion analysis,and provides theoretical and practical references for risk forecasting, spatial resilience enhancement,and collaborative opinion governance in rural micro-nodes.