Misinformation spreading on activity-driven networks with heterogeneous spreading rates.

Abstract

The spread of misinformation on social media is inextricably related to each user's forwarding habits. In this paper, given that users have heterogeneous forwarding probabilities to their neighbors with varied relationships when they receive misinformation, we present a novel ignorant-spreader-refractory (ISR) spreading model with heterogeneous spreading rates on activity-driven networks with various types of links that encode these differential relationships. More exactly, in this model, the same type of links has an identical spreading rate, while different types of links have distinct ones. Using a mean-field approach and Monte Carlo simulations, we investigate how the heterogeneity of spreading rates affects the outbreak threshold and final prevalence of misinformation. It is demonstrated that the heterogeneity of spreading rates has no effect on the threshold when the type of link follows a uniform distribution. However, it has a significant impact on the threshold for non-uniform distributions. For example, the heterogeneity of spreading rates increases the threshold for normal distribution while it lowers the threshold for an exponent distribution. In comparison to the situation of a homogeneous spreading rate, whether the heterogeneity of spreading rates improves or decreases the final prevalence of misinformation is also determined by the distributions of the type of links.