论文标题
在地方网络中使用图案特性来表征城市生活方式签名
Characterizing Urban Lifestyle Signatures Using Motif Properties in Network of Places
论文作者
论文摘要
城市居民的生活方式可以揭示有关城市动态和复杂性的重要见解。尽管对城市生活方式模式的分析进行了越来越多的研究，但对城市规模上人们的生活方式模式的特征知之甚少。这种限制主要是由于当汇总人类运动数据以保护用户的隐私时表征生活方式模式的挑战。在这项研究中，我们基于汇总的人类访问数据来对城市进行建模，以构建一个地方网络。然后，我们检查地点网络中的子图标志，以绘制和表征城市规模的生活方式模式。检查了来自哈里斯县，达拉斯县，纽约县和美国布劳沃德县的位置数据，以揭示城市的生活方式签名。为了进行主题分析，从人类访问网络中提取了没有位置属性的两个节点，三节点和四个节点基序。其次，将基序中的均质节点与NAICS代码的位置类别进行编码。量化了多种统计措施，包括网络指标和主题属性，以表征生活方式签名。结果表明：可以根据位置网络中图案的分布和属性来很好地描绘和量化城市环境中人们的生活方式；地方网络中的图案在周末和工作日的数量和距离表现出稳定性，表明城市生活方式模式的稳定性；人类探视网络和生活方式模式在不同的大都市地区显示出相似之处，这意味着整个城市的生活方式签名的普遍性。这些发现为城市研究中的城市生活方式签名提供了更深入的见解，并为数据知识的城市规划和管理提供了重要的见解。
The lifestyles of urban dwellers could reveal important insights regarding the dynamics and complexity of cities. Despite growing research on analysis of lifestyle patterns in cities, little is known about the characteristics of people's lifestyles patterns at urban scale. This limitation is primarily due to challenges in characterizing lifestyle patterns when human movement data is aggregated to protect the privacy of users. In this study, we model cities based on aggregated human visitation data to construct a network of places. We then examine the subgraph signatures in the networks of places to map and characterize lifestyle patterns at city scale. Location-based data from Harris County, Dallas County, New York County, and Broward County in the United States were examined to reveal lifestyle signatures in cities. For the motif analysis, two-node, three-node, and four-node motifs without location attributes were extracted from human visitation networks. Second, homogenized nodes in motifs were encoded with location categories from NAICS codes. Multiple statistical measures, including network metrics and motif properties, were quantified to characterize lifestyle signatures. The results show that: people's lifestyles in urban environments can be well depicted and quantified based on distribution and attributes of motifs in networks of places; motifs in networks of places show stability in quantity and distance as well as periodicity on weekends and weekdays indicating the stability of lifestyle patterns in cities; human visitation networks and lifestyle patterns show similarities across different metropolitan areas implying the universality of lifestyle signatures across cities. The findings provide deeper insights into urban lifestyles signatures in urban studies and provide important insights for data-informed urban planning and management.
