College of Architecture and Urban Planning, Tongji University, Shanghai, P. R. China.
The Bartlett Centre for Advanced Spatial Analysis, University College London, London, United Kingdom.
PLoS One. 2019 Feb 11;14(2):e0212004. doi: 10.1371/journal.pone.0212004. eCollection 2019.
Urban public spaces facilitate social interactions between people, reflecting the shifting functionality of spaces. There is no commonly-held consensus on the quantification methods for the dynamic interplay between spatial geometry, urban movement, and face-to-face encounters. Using anonymized social media check-in records from Shanghai, China, this study proposes pipelines for quantifying physical face-to-face encounter potential patterns through public space networks between local and non-local residents sensed by social media over time from space to space, in which social difference, cognitive cost, and time remoteness are integrated as the physical co-presence intensity index. This illustrates the spatiotemporally different ways in which the built environment binds various groups of space users configurationally via urban streets. The variation in face-to-face interaction patterns captures the fine-resolution patterns of urban flows and a new definition of street hierarchy, illustrating how urban public space systems deliver physical meeting opportunities and shape the spatial rhythms of human behavior from the public to the private. The shifting encounter potentials through streets are recognized as reflections of urban centrality structures with social interactions that are spatiotemporally varying, projected in the configurations of urban forms and functions. The results indicate that the occurrence probability of face-to-face encounters is more geometrically scaled than predicted based on the co-location probability of two people using metric distance alone. By adding temporal and social dimensions to urban morphology studies, and the field of space syntax research in particular, we suggest a new approach of analyzing the temporal urban centrality structures of the physical interaction potentials based on trajectory data, which is sensitive to the transformation of the spatial grid. It sheds light on how to adopt urban design as a social instrument to facilitate the dynamically changing social interaction potential in the new data environment, thereby enhancing spatial functionality and the social well-being.
城市公共空间促进了人与人之间的社会互动，反映了空间功能的转变。目前，对于空间几何、城市流动和面对面交流之间的动态相互作用的量化方法，还没有达成共识。本研究使用来自中国上海的匿名社交媒体签到记录，提出了通过社交媒体随时间从一个空间到另一个空间感知到的本地和非本地居民之间的公共空间网络来量化物理面对面接触潜力模式的管道，其中社会差异、认知成本和时间距离被整合为物理共存强度指数。这说明了通过城市街道，建筑环境在空间上不同地将各种空间用户群体配置性地联系起来的方式。面对面互动模式的变化捕捉到了城市流动的细分辨率模式和街道层次结构的新定义，说明了城市公共空间系统如何从公共空间到私人空间提供物理会面机会并塑造人类行为的空间节奏。通过街道的不断变化的相遇潜力被认为是反映具有时空变化的社会互动的城市中心结构的反映，这些互动体现在城市形态和功能的配置中。结果表明，面对面相遇的发生概率比仅根据两个人的共定位概率用度量距离预测的更符合几何比例。通过在城市形态研究中加入时间和社会维度，特别是在空间句法研究领域，我们提出了一种基于轨迹数据分析物理相互作用潜力的时间城市中心结构的新方法，该方法对空间网格的转换很敏感。它揭示了如何采用城市设计作为一种社会手段，在新的数据环境中促进不断变化的社会互动潜力，从而增强空间功能和社会幸福感。
