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Empirical study of the role of the topology in spreading on communication networks

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  • Medvedev, Alexey
  • Kertesz, Janos

Abstract

Topological aspects, like community structure, and temporal activity patterns, like burstiness, have been shown to severely influence the speed of spreading in temporal networks. We study the influence of the topology on the susceptible–infected (SI) spreading on time stamped communication networks, as obtained from a dataset of mobile phone records. We consider city level networks with intra- and inter-city connections. The networks using only intra-city links are usually sparse, where the spreading depends mainly on the average degree. The inter-city links serve as bridges in spreading, speeding up considerably the process. We demonstrate the effect also on model simulations.

Suggested Citation

  • Medvedev, Alexey & Kertesz, Janos, 2017. "Empirical study of the role of the topology in spreading on communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 12-19.
    • Handle: RePEc:eee:phsmap:v:470:y:2017:i:c:p:12-19
    DOI: 10.1016/j.physa.2016.11.109
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    References listed on IDEAS

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    Cited by:

    1. Xu, Xiao-Ting & Wang, Nianxin & Bian, Jun & Zhou, Bin, 2019. "Understanding the diversity on power-law-like degree distribution in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 576-581.
    2. Tu, Haicheng & Xia, Yongxiang & Wu, Jiajing & Zhou, Xiang, 2019. "Robustness assessment of cyber–physical systems with weak interdependency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 9-17.
    3. Fei, Liguo & Zhang, Qi & Deng, Yong, 2018. "Identifying influential nodes in complex networks based on the inverse-square law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1044-1059.
    4. Huang, Wei & Zhang, Tianyi & Yao, Xinwei, 2022. "Optimization for sequential communication line attack in interdependent power-communication network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    5. Zhou, Bin & Xu, Xiao-Ting & Liu, Jian-Guo & Xu, Xiao-Ke & Wang, Nianxin, 2019. "Information interaction model for the mobile communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1170-1176.

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