Towards Merging Models of Information Spreading and Dynamic Phenomena in Social Networks

Abstract : While the impact of network properties on information spread- ing is now widely studied, in uence of network dynamics is very little known. In this paper, we study how evolution mechanisms tradition- ally observed within social networks can a ect information di usion. We present an approach that merges two models: model of informa- tion di usion through social networks and model of network evolution. Since epidemics provide a reference in application domains of information spreading, we measure the impact of basic network structure changes on epidemic peak value and timing. Then we investigate observed trends in terms of changes appearing in the network structure. Our results provide promising results on how and why network dynamics is a strong param- eter to integrate in requirements for information spreading modelling.
Type de document :
Communication dans un congrès
Springer. World Summit on the Knowledge Society (WSKS), 2011, Mykonos, Greece. pp.1-9, 2011
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https://hal.archives-ouvertes.fr/hal-00768405
Contributeur : Erick Stattner <>
Soumis le : vendredi 21 décembre 2012 - 14:06:22
Dernière modification le : lundi 21 mars 2016 - 17:28:33

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  • HAL Id : hal-00768405, version 1

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Erick Stattner, Martine Collard, Nicolas Vidot. Towards Merging Models of Information Spreading and Dynamic Phenomena in Social Networks. Springer. World Summit on the Knowledge Society (WSKS), 2011, Mykonos, Greece. pp.1-9, 2011. 〈hal-00768405〉

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