Abstract
The information diffusion and the influence propagation in an online social network behave similar to the epidemic process and have been studied through the classic epidemiological models. The epidemic threshold is a fundamental metric for the epidemic process to determine the condition when an epidemic can either survive or die out in a network. The previous works have been focused on finding the epidemic threshold when both infection rates and recovery rates are homogeneous or studying the transient behavior of an epidemic when the infection rates are heterogeneous. In this work, we explore the effect of the heterogeneity in both infection rates and recovery rates on the epidemic threshold through both analysis and simulations. We discover that heterogeneous infection rates and heterogeneous recovery rates have the opposite impact on the epidemic threshold. Specifically, the heterogeneity in infection rates leads to a larger epidemic threshold than in the homogeneous case. Moreover, as the degree of the heterogeneity of infection rates gets higher, the epidemic threshold increases. On the other hand, the heterogeneity in recovery rates generates a smaller epidemic threshold than in the homogeneous case. Furthermore, the epidemic threshold decreases as the degree of the heterogeneity of recovery rates gets higher.
Published Version
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