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Social Network Analysis and Mining

, Volume 3, Issue 4, pp 1195–1208 | Cite as

Inadequacy of SIR model to reproduce key properties of real-world spreading cascades: experiments on a large-scale P2P system

  • Daniel F. BernardesEmail author
  • Matthieu Latapy
  • Fabien Tarissan
Original Article

Abstract

Understanding the spread of information on complex networks is a key issue from a theoretical and applied perspective. Despite the effort in developing theoretical models for this phenomenon, gauging them with large-scale real-world data remains an important challenge due to the scarcity of open, extensive and detailed data. In this paper, we explain how traces of peer-to-peer file sharing may be used to reach this goal. We reconstruct the underlying social network of peers sharing content and perform simulations on it to assess the relevance of the standard SIR model to mimic key properties of real spreading cascades. First, we examine the impact of the network topology on observed properties. Then we turn to the evaluation of two heterogeneous extensions of the SIR model. Finally, we improve the social network reconstruction, introducing an affinity index between peers, and simulate a SIR model which integrates this new feature. We conclude that the simple, homogeneous model is insufficient to mimic real spreading cascades. Moreover, none of the natural extensions of the model we considered, which take into account extra topological properties, yielded satisfying results in our context. This raises an alert against the careless, widespread use of this model.

Keywords

Bipartite Graph Random Graph Degree Distribution File Sharing Infected Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This work is partly funded by the European Commission through the FP7-FIRE project EULER (Grant No.258307) and by the City of Paris Emergence program through the DiRe project.

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Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • Daniel F. Bernardes
    • 1
    Email author
  • Matthieu Latapy
    • 1
  • Fabien Tarissan
    • 1
  1. 1.LIP6, CNRS and Université Pierre et Marie Curie/Paris 6Paris Cedex 05France

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