Rumor spreading model considering rumor credibility, correlation and crowd classification based on personality

Abstract

AbstractThe study of rumor spreading or rumor controlling is important and necessary because rumors can cause serious negative effects on society. The process of rumor spreading is influenced by many factors. In this paper, we suggest that people with different personalities will behave differently after hearing rumors. Thus, we divide the population into two types: radical people and steady people. Furthermore, we suggest that the credibility of rumors and the correlation between rumors and people’s lives are important factors that will influence the spread of rumors. Based on these considerations, we propose the SEIsIrR model. We establish differential equations to describe the dynamics of the rumor spreading process in homogeneous and heterogeneous networks. Using the Jacobian matrix and next generation matrix, we obtain the spreading threshold of the SEIsIrR model and discuss the relationship of the spreading threshold between homogeneous networks and heterogeneous networks. We employ a real rumor dataset obtained from Twitter to verify the SEIsIrR model and perform numerical simulations in Watts-Strogatz (WS) networks and Barabasi-Albert (BA) networks to verify the obtained spreading thresholds and discuss the impacts of these factors on the rumor spreading process and the differences in the rumor spreading processes between WS networks and BA networks. The simulation results show that these factors influence the speed and range of rumor spreading.