Diffusion in Dynamic Social Networks: Application in Epidemiology

  • Erick Stattner
  • Martine Collard
  • Nicolas Vidot
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6861)


Structure and evolution of networks have been areas of growing interest in recent years, especially with the emergence of Social Network Analysis (SNA) and its application in numerous fields. Researches on diffusion are focusing on network modeling for studying spreading phenomena. While the impact of network properties on spreading is now widely studied, involvement of network dynamicity is very little known. In this paper, we address the epidemiology context and study the consequences of network evolutions on spread of diseases. Experiments are conducted by comparing incidence curves obtained by evolution strategies applied on two generated and two real networks. Results are then analyzed by investigating network properties and discussed in order to explain how network evolution influences the spread. We present the MIDEN framework, an approach to measure impact of basic changes in network structure, and DynSpread, a 2D simulation tool designed to replay infections scenarios on evolving networks.


Information Spreading Dynamic network Evolution Framework Simulation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Erick Stattner
    • 1
  • Martine Collard
    • 1
  • Nicolas Vidot
    • 1
  1. 1.LAMIA LaboratoryUniversity of the French West Indies and GuianaFrance

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