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The dynamics of a mobile phone network

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  • Hidalgo, Cesar A.
  • Rodriguez-Sickert, C.

Abstract

The empirical study of network dynamics has been limited by the lack of longitudinal data. Here we introduce a quantitative indicator of link persistence to explore the correlations between the structure of a mobile phone network and the persistence of its links. We show that persistent links tend to be reciprocal and are more common for people with low degree and high clustering. We study the redundancy of the associations between persistence, degree, clustering and reciprocity and show that reciprocity is the strongest predictor of tie persistence. The method presented can be easily adapted to characterize the dynamics of other networks and can be used to identify the links that are most likely to survive in the future.

Suggested Citation

  • Hidalgo, Cesar A. & Rodriguez-Sickert, C., 2008. "The dynamics of a mobile phone network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3017-3024.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:12:p:3017-3024
    DOI: 10.1016/j.physa.2008.01.073
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    Citations

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    Cited by:

    1. Tang, Jinjun & Liu, Fang & Wang, Yinhai & Wang, Hua, 2015. "Uncovering urban human mobility from large scale taxi GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 140-153.
    2. Santi Phithakkitnukoon & Zbigniew Smoreda & Patrick Olivier, 2012. "Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
    3. McBride, Neal & Bulava, John & Galiotto, Carlo & Marchetti, Nicola & Macaluso, Irene & Doyle, Linda, 2017. "Degeneracy estimation in interference models on wireless networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 540-550.
    4. Karimi, Fariba & Ramenzoni, Verónica C. & Holme, Petter, 2014. "Structural differences between open and direct communication in an online community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 263-273.
    5. Wang, Xi & Pei, Tao & Song, Ci & Chen, Jie & Shu, Hua & Liu, Yaxi & Guo, Sihui & Chen, Xiao, 2023. "How does socioeconomic status influence social relations? A perspective from mobile phone data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    6. Park, Ji Hwan & Chang, Woojin & Song, Jae Wook, 2020. "Link prediction in the Granger causality network of the global currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    7. Uchida, Makoto & Shirayama, Susumu, 2008. "Influence of a network structure on the network effect in the communication service market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5303-5310.
    8. Andreas Spitz & Emőke-Ágnes Horvát, 2014. "Measuring Long-Term Impact Based on Network Centrality: Unraveling Cinematic Citations," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
    9. Adam M. Kleinbaum, 2018. "Reorganization and Tie Decay Choices," Management Science, INFORMS, vol. 64(5), pages 2219-2237, May.
    10. Ashwin Bahulkar & Boleslaw K. Szymanski & Nitesh Chawla & Omar Lizardo & Kevin Chan, 2017. "Influence of Personal Preferences on Link Dynamics in Social Networks," Complexity, Hindawi, vol. 2017, pages 1-12, September.
    11. Li, Mingwu & Dankowicz, Harry, 2019. "Impact of temporal network structures on the speed of consensus formation in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1355-1370.
    12. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    13. Owczarczuk, Marcin, 2012. "Long memory in patterns of mobile phone usage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1428-1433.
    14. He, Kun & Xu, Zhongzhi & Wang, Pu, 2015. "A hybrid routing model for mitigating congestion in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 1-17.
    15. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    16. Tang, Jinjun & Zhang, Shen & Zhang, Wenhui & Liu, Fang & Zhang, Weibin & Wang, Yinhai, 2016. "Statistical properties of urban mobility from location-based travel networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 694-707.
    17. Han Wang & Damien Fay & Kenneth N. Brown & Liam Kilmartin, 2016. "Modelling revenue generation in a dynamically priced mobile telephony service," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(4), pages 711-734, August.
    18. 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.
    19. Philip Salesses & Katja Schechtner & César A Hidalgo, 2013. "The Collaborative Image of The City: Mapping the Inequality of Urban Perception," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.

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