Uncovering regional characteristics from mobile phone data: A network science approach

Guanghua Chi, Jean Claude Thill, Daoqin Tong, Li Shi, Yu Liu

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


We introduce network science methods to uncover inherent characteristics of functional regions. An aggregate spatial interaction network is constructed based on a large mobile phone data set including 431 million mobile calls made by 10 million anonymous customers over one month and the geographic locations of the mobile base towers involved in each call. We use Thiessen polygons (termed ‘cells’) as the unit of analysis to approximate the service area of each mobile base tower. Major findings encompass the following three aspects. First, cells with high betweenness centrality are linearly distributed in space, which closely aligns with major transportation corridors. We find that this pattern can be explained by analysing the characteristics of calling activities on transportation networks. Second, we detect a two-level hierarchy of communities that correspond well to county and prefecture-level administrative unit boundaries. Lastly, almost every community identified at the two hierarchical levels contains a cell with high betweenness. These cells are located near the political and economic centres and play the role of hubs in the regional socio-economic system. This research demonstrates that networks built from mobile phone data provide new understandings of spatial interactions and regional structures.

Original languageEnglish (US)
Pages (from-to)613-631
Number of pages19
JournalPapers in Regional Science
Issue number3
StatePublished - Aug 1 2016
Externally publishedYes


  • Spatial network
  • betweenness centrality
  • community detection
  • mobile phone data
  • regional structure

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Environmental Science (miscellaneous)


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