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Emergence of encounter networks due to human mobility

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  • A P Riascos
  • José L Mateos

Abstract

There is a burst of work on human mobility and encounter networks. However, the connection between these two important fields just begun recently. It is clear that both are closely related: Mobility generates encounters, and these encounters might give rise to contagion phenomena or even friendship. We model a set of random walkers that visit locations in space following a strategy akin to Lévy flights. We measure the encounters in space and time and establish a link between walkers after they coincide several times. This generates a temporal network that is characterized by global quantities. We compare this dynamics with real data for two cities: New York City and Tokyo. We use data from the location-based social network Foursquare and obtain the emergent temporal encounter network, for these two cities, that we compare with our model. We found long-range (Lévy-like) distributions for traveled distances and time intervals that characterize the emergent social network due to human mobility. Studying this connection is important for several fields like epidemics, social influence, voting, contagion models, behavioral adoption and diffusion of ideas.

Suggested Citation

  • A P Riascos & José L Mateos, 2017. "Emergence of encounter networks due to human mobility," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-22, October.
    • Handle: RePEc:plo:pone00:0184532
    DOI: 10.1371/journal.pone.0184532
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    References listed on IDEAS

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    1. Baronchelli, Andrea & Radicchi, Filippo, 2013. "Lévy flights in human behavior and cognition," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 101-105.
    2. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
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    Cited by:

    1. Wu, Wenbo & Dong, Bing & Wang, Qi (Ryan) & Kong, Meng & Yan, Da & An, Jingjing & Liu, Yapan, 2020. "A novel mobility-based approach to derive urban-scale building occupant profiles and analyze impacts on building energy consumption," Applied Energy, Elsevier, vol. 278(C).
    2. Jincheng Jiang & Jinsong Chen & Wei Tu & Chisheng Wang, 2019. "A Novel Effective Indicator of Weighted Inter-City Human Mobility Networks to Estimate Economic Development," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    3. Liu, Kang & Yin, Ling & Ma, Zhanwu & Zhang, Fan & Zhao, Juanjuan, 2020. "Investigating physical encounters of individuals in urban metro systems with large-scale smart card data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Zhu, Kangli & Yin, Haodong & Qu, YunChao & Wu, Jianjun, 2021. "Group travel behavior in metro system and its relationship with house price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    5. Rebecca D. Merrill & Ali Imorou Bah Chabi & Elvira McIntyre & Jules Venance Kouassi & Martial Monney Alleby & Corrine Codja & Ouyi Tante & Godjedo Togbemabou Primous Martial & Idriss Kone & Sarah Ward, 2021. "An approach to integrate population mobility patterns and sociocultural factors in communicable disease preparedness and response," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.

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