Diffusion in Dynamic Social Networks: Application in Epidemiology

Abstract : 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.
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Communication dans un congrès
Springer. Database and Expert Systems Applications - 22nd International Conference, DEXA 2011, 2011, Toulouse, France. 6861 (2), pp.559-573, 2011, Lecture Notes in Computer Science. 〈10.1007/978-3-642-23091-2_49〉
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https://hal.archives-ouvertes.fr/hal-00614925
Contributeur : Erick Stattner <>
Soumis le : mercredi 17 août 2011 - 14:16:32
Dernière modification le : lundi 21 mars 2016 - 17:39:01

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Erick Stattner, Martine Collard, Nicolas Vidot. Diffusion in Dynamic Social Networks: Application in Epidemiology. Springer. Database and Expert Systems Applications - 22nd International Conference, DEXA 2011, 2011, Toulouse, France. 6861 (2), pp.559-573, 2011, Lecture Notes in Computer Science. 〈10.1007/978-3-642-23091-2_49〉. 〈hal-00614925〉

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