Dataset Information

Understanding metropolitan patterns of daily encounters.

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.

SUBMITTER: Sun L

PROVIDER: S-EPMC3752247 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Understanding metropolitan patterns of daily encounters.

Sun Lijun L Axhausen Kay W KW Lee Der-Horng DH Huang Xianfeng X

Proceedings of the National Academy of Sciences of the United States of America 20130805 34

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 displa ...[more]

PMID: 23918373

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Dataset Information

Understanding metropolitan patterns of daily encounters.

Publications

Understanding metropolitan patterns of daily encounters.

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