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Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator

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  • Sanja Šćepanović
  • Igor Mishkovski
  • Pan Hui
  • Jukka K Nurminen
  • Antti Ylä-Jääski

Abstract

The advent of publishing anonymized call detail records opens the door for temporal and spatial human dynamics studies. Such studies, besides being useful for creating universal models for mobility patterns, could be also used for creating new socio-economic proxy indicators that will not rely only on the local or state institutions. In this paper, from the frequency of calls at different times of the day, in different small regional units (sub-prefectures) in Côte d'Ivoire, we infer users' home and work sub-prefectures. This division of users enables us to analyze different mobility and calling patterns for the different regions. We then compare how those patterns correlate to the data from other sources, such as: news for particular events in the given period, census data, economic activity, poverty index, power plants and energy grid data. Our results show high correlation in many of the cases revealing the diversity of socio-economic insights that can be inferred using only mobile phone call data. The methods and the results may be particularly relevant to policy-makers engaged in poverty reduction initiatives as they can provide an affordable tool in the context of resource-constrained developing economies, such as Côte d'Ivoire's.

Suggested Citation

  • Sanja Šćepanović & Igor Mishkovski & Pan Hui & Jukka K Nurminen & Antti Ylä-Jääski, 2015. "Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    • Handle: RePEc:plo:pone00:0124160
    DOI: 10.1371/journal.pone.0124160
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    References listed on IDEAS

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    Cited by:

    1. Jian Gao & Tao Zhou, 2017. "Quantifying China's Regional Economic Complexity," Papers 1703.01292, arXiv.org, revised Nov 2017.
    2. Liu, Jin-Hu & Wang, Jun & Shao, Junming & Zhou, Tao, 2016. "Online social activity reflects economic status," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 581-589.
    3. Erlström, Andreas & Grillitsch, Markus & Hall, Ola, 2020. "The Geography of Connectivity: Trails of Mobile Phone Data," Papers in Innovation Studies 2020/6, Lund University, CIRCLE - Centre for Innovation Research.
    4. Chen, Ya & Li, Xue & Zhang, Richong & Huang, Zi-Gang & Lai, Ying-Cheng, 2020. "Instantaneous success and influence promotion in cyberspace — how do they occur?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).

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