Public Space Optimization Strategy Through Social Network Analysis in Shenzhen’s Gongming Ancient Fair - Hang Ma; Mohan Wang; Jinqi Li; Han Liu (Land, 2025)
Ancient fairs in China were designated as commercial zones with fixed stalls that had emerged from commodity exchange demands and socio-cultural factors such as clan systems and gentry intervention, exhibiting dual commercial–communal characteristics. Several ancient fairs in Shenzhen have been retained, including Gongming Ancient Fair, which maintains its original spatial configuration adjacent to industrial zones and urban villages, attracting a high concentration of migrant workers. Survey results show that 85% of Gongming residents demand public space renovations, citing inadequacy of the spaces to support public activities. Given the intrinsic link between public spaces and public activities, fostering their positive interaction is crucial for enhancing urban vitality. However, existing studies predominantly focus on the physical environment and neglect activity-driven optimization perspectives. This study first employed social network analysis (SNA) to construct two networks of Gongming Ancient Fair, using the software Ucinet 6.755, including a public space network based on spatial connectivity and a public activity network based on pedestrian flow. Second, the networks’ structural characteristics were analyzed using seven metrics: node degree, density, betweenness centrality, betweenness centralization, clustering coefficient, average path length, and small-world property. Discrepancies between the networks were quantified through betweenness centrality comparisons, with field surveys and interviews identifying causal factors including seasonal product limitations, spatial constraints, inadequate supporting facilities, and substandard management. Based on the survey data and analytical results, the key renovation nodes were categorized into three types: high-control-capacity nodes, high-expectation nodes, and culturally distinctive nodes. Finally, three optimization strategies are proposed. This study integrates sociological perspectives into ancient fair revitalization, addressing gaps in activity-driven spatial research.