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Diffusion in Dynamic Social Networks: Application in Epidemiology

Identifieur interne : 002299 ( Main/Exploration ); précédent : 002298; suivant : 002300

Diffusion in Dynamic Social Networks: Application in Epidemiology

Auteurs : Erick Stattner [France] ; Martine Collard [France] ; Nicolas Vidot [France]

Source :

RBID : ISTEX:821BA55B3AA26FF8B09F4505AD9175B5D3E587F1

Abstract

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.

Url:
DOI: 10.1007/978-3-642-23091-2_49


Affiliations:


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