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理解日常相遇的大都市模式。

Understanding metropolitan patterns of daily encounters.

机构信息

Future Cities Laboratory, Singapore-ETH Centre for Global Environmental Sustainability, Singapore 138602.

出版信息

Proc Natl Acad Sci U S A. 2013 Aug 20;110(34):13774-9. doi: 10.1073/pnas.1306440110. Epub 2013 Aug 5.

Abstract

Understanding of the mechanisms driving our daily face-to-face encounters is still limited; the field lacks large-scale datasets describing both individual behaviors and their collective interactions. However, here, with the help of travel smart card data, we uncover such encounter mechanisms and structures by constructing a time-resolved in-vehicle social encounter network on public buses in a city (about 5 million residents). Using a population scale dataset, we find physical encounters display reproducible temporal patterns, indicating that repeated encounters are regular and identical. On an individual scale, we find that collective regularities dominate distinct encounters' bounded nature. An individual's encounter capability is rooted in his/her daily behavioral regularity, explaining the emergence of "familiar strangers" in daily life. Strikingly, we find individuals with repeated encounters are not grouped into small communities, but become strongly connected over time, resulting in a large, but imperceptible, small-world contact network or "structure of co-presence" across the whole metropolitan area. Revealing the encounter pattern and identifying this large-scale contact network are crucial to understanding the dynamics in patterns of social acquaintances, collective human behaviors, and--particularly--disclosing the impact of human behavior on various diffusion/spreading processes.

摘要

我们对推动日常面对面接触的机制的理解仍然有限;该领域缺乏描述个体行为及其集体相互作用的大规模数据集。然而,在这里,借助出行智能卡数据,我们通过构建城市公共汽车上的实时车内社会接触网络(约 500 万居民)来揭示这些接触机制和结构。使用人口规模数据集,我们发现身体接触呈现可重复的时间模式,表明重复接触是有规律且相同的。在个体层面上,我们发现集体规律主导着不同接触的有限性质。个体的接触能力源于其日常行为的规律性,这解释了日常生活中“熟悉的陌生人”的出现。引人注目的是,我们发现有重复接触的个体并没有被分成小团体,而是随着时间的推移变得紧密相连,从而在整个大都市区形成了一个庞大但难以察觉的小世界接触网络或“共同存在的结构”。揭示接触模式并识别这种大规模的接触网络对于理解社交熟人模式的动态、集体人类行为以及——特别是——揭示人类行为对各种扩散/传播过程的影响至关重要。

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