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Understanding the effects of administrative boundary in sampling spatially embedded networks

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  • Chi, Guanghua
  • Liu, Yu
  • Shi, Li
  • Gao, Yong

Abstract

When analyzing spatially embedded networks, networks consisting of nodes and connections within an administrative boundary are commonly analyzed directly without considering possible errors or biases due to lost connections to nodes outside the network. However, connections exist not only within administrative boundaries but also to nodes outside of the boundaries. This study empirically analyzed the geographical boundary problem using a mobile communication network constructed based on mobile phone data collected in Heilongjiang province, China. We find that although many connections outside of the administrative boundary are lost, sampled networks based on administrative boundaries perform relatively well in terms of degree and clustering coefficient. We find that the mechanisms behind the reliability of these sampled networks include the effects of distance decay and cohesion strength in administrative regions on spatially embedded networks.

Suggested Citation

  • Chi, Guanghua & Liu, Yu & Shi, Li & Gao, Yong, 2017. "Understanding the effects of administrative boundary in sampling spatially embedded networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 616-625.
    • Handle: RePEc:eee:phsmap:v:466:y:2017:i:c:p:616-625
    DOI: 10.1016/j.physa.2016.09.023
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    References listed on IDEAS

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    1. Carlo Ratti & Stanislav Sobolevsky & Francesco Calabrese & Clio Andris & Jonathan Reades & Mauro Martino & Rob Claxton & Steven H Strogatz, 2010. "Redrawing the Map of Great Britain from a Network of Human Interactions," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-6, December.
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    3. Guanghua Chi & Jean-Claude Thill & Daoqin Tong & Li Shi & Yu Liu, 2016. "Uncovering regional characteristics from mobile phone data: A network science approach," Papers in Regional Science, Wiley Blackwell, vol. 95(3), pages 613-631, August.
    4. 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.
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