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Bursty visitation of locations in human mobility

Author

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  • Lv, Junyu
  • Zhao, Chen
  • Zeng, An

Abstract

Understanding individuals’ travel patterns has great impact on practical issues such as traffic control and urban planning. Here, we analyze a 4G dataset of 1000 randomly selected individuals in Shijiazhuang city, China during half month which contains the position information of these cell phone users in each second and GPS logs of 182 volunteers in a period of over five years. We find that the dynamics of locations’ visitations is characterized by bursts, namely the distributions of the relative variation of visitation traffic per day, week display a long tail. On that basis we propose the Exploration and Rank-shift Return model combined the classic Exploration and Preferential Return model with a rank-shift mechanism where every location may move up to a higher ranking position with probability. The model qualitatively recovers the statistical properties observed in the empirical data and reproduces the existence of bursty visitation of locations.

Suggested Citation

  • Lv, Junyu & Zhao, Chen & Zeng, An, 2021. "Bursty visitation of locations in human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    • Handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120309729
    DOI: 10.1016/j.physa.2020.125674
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    Cited by:

    1. Li, Xianghua & Deng, Yue & Yuan, Xuesong & Wang, Zhen & Gao, Chao, 2022. "Data-driven behavioral analysis and applications: A case study in Changchun, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).

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