Effects of Inoculation Based on Structural Centrality on Rumor Dynamics in Social Networks
In social networks, the mechanism to suppress harmful rumors is of great importance. A rumor spreading model has been defined using the susceptible-infected-refractory (SIR) model to characterize rumor propagation in social networks. In this paper a new inoculation strategy based on structural centrality has been applied on rumor spreading model for heterogeneous networks. It is compared with the targeted and random inoculations. The structural centrality of each nodes has been ranked in the topology of social networks which is modeled as scale free network. The nodes with higher structural centrality are chosen for inoculation in the proposed strategy. The structural centrality based inoculation strategy is more efficient in comparison with the random and targeted inoculation strategies. One of the bottlenecks is the high complexity to calculate the structural centrality of the nodes for very large number of nodes in the complex networks. The proposed hypothesis has been verified using simulation results for email network data and the generated scale free networks.
KeywordsComplex networks graph spectra rumor spreading model inoculation strategies
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