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Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

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  • Yu Liu
  • Zhengwei Sui
  • Chaogui Kang
  • Yong Gao

Abstract

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.

Suggested Citation

  • Yu Liu & Zhengwei Sui & Chaogui Kang & Yong Gao, 2014. "Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
  • Handle: RePEc:plo:pone00:0086026
    DOI: 10.1371/journal.pone.0086026
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    References listed on IDEAS

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    1. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    2. Anastasios Noulas & Salvatore Scellato & Renaud Lambiotte & Massimiliano Pontil & Cecilia Mascolo, 2012. "A Tale of Many Cities: Universal Patterns in Human Urban Mobility," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-10, May.
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