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This study, taking Beijing Shougang Park as a case, analyzes the public spaces after industrial heritage renovation and explores the relationship between industrial heritage spaces and residents’ activities based on residents’ spatial behaviours. The study introduces Social Network Analysis (SNA) to construct both a public space network model and a residents’ spatial behaviour network model, integrating them through network metrics. The findings indicate that Shougang Park follows a centralized cluster-based layout, creating diverse spatial experiences through ‘multi-point aggregation, path connectivity, and regional integration’. Residents’ spatial behaviours exhibit a ‘core periphery’ structure, showing clear preferences for industrial heritage elements, natural landscapes, and open plazas, thereby forming a ‘check-in’ style touring pattern along the main axis connecting spatial clusters. Based on these insights, the study proposes targeted spatial optimization strategies. The results demonstrate that SNA can quantify the relationship between industrial heritage spaces and behaviours, revealing a bidirectional mechanism: spatial layout influences residents’ behaviour choices, while residents’ behaviours, in turn, shape new patterns of space use and generate shortcuts. This further indicates that understanding residents’ spatial behaviours can provide practical guidance for the planning and renovation of industrial heritage public spaces.
Cao et al. (Mon,) studied this question.