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From calls to communities: a model for time-varying social networks

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  • Guillaume Laurent
  • Jari Saramäki
  • Márton Karsai

Abstract

Social interactions vary in time and appear to be driven by intrinsic mechanisms that shape the emergent structure of social networks. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model integrates key mechanisms that drive the formation of social ties – social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and small-world connectedness in social networks. We compare the proposed model with a real-world time-varying network of mobile phone communication, and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, including the role of weak ties. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Guillaume Laurent & Jari Saramäki & Márton Karsai, 2015. "From calls to communities: a model for time-varying social networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(11), pages 1-10, November.
  • Handle: RePEc:spr:eurphb:v:88:y:2015:i:11:p:1-10:10.1140/epjb/e2015-60481-x
    DOI: 10.1140/epjb/e2015-60481-x
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    Cited by:

    1. Karan, Rituraj & Biswal, Bibhu, 2017. "A model for evolution of overlapping community networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 380-390.
    2. He, Jialin & Chen, Duanbing & Sun, Chongjing & Fu, Yan & Li, Wenjun, 2017. "Efficient stepwise detection of communities in temporal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 438-446.

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