This work aims to explore the community structure of Santiago de Chile by analyzing the movement patterns of its residents. We use a dataset containing the approximate locations of home and work places for a subset of anonymized residents to construct a network that represents the movement patterns within the city. Through the analysis of this network, we aim to identify the communities or sub-cities that exist within Santiago de Chile and gain insights into the factors that drive the spatial organization of the city. We employ modularity optimization algorithms and clustering techniques to identify the communities within the network. Our results present that the novelty of combining community detection algorithms with segregation tools provides new insights to further the understanding of the complex geography of segregation during working hours.

翻译：本研究旨在通过分析圣地亚哥居民的移动模式，探究其社区结构。我们使用一个包含匿名居民子集的工作与居住地近似位置的数据集，构建了代表城市内部移动模式的网络。通过分析该网络，我们试图识别圣地亚哥内存在的社区或子城市，并深入了解推动城市空间组织的因素。我们采用模块度优化算法与聚类技术来识别网络中的社区。结果表明，社区检测算法与隔离工具的创新结合，为理解工作时段复杂隔离地理现象提供了新的视角。