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

While the impact of network properties on information spreading is now widely studied, influence of network dynamics is very little known. In this paper, we study how evolution mechanisms traditionally observed within social networks can affect information diffusion. We present an approach that merges two models: model of information diffusion 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 parameter to integrate in requirements for information spreading modelling.

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