Modeling and Simulation of Opinion Natural Reversal Dynamics with Opinion Leader Based on HK Bounded Confidence Model

Abstract

Opinion natural reversals are important and common phenomena in network management. It is a naturally emerging process of opinions characterized by interactions between individuals and the evolution of attitudes themselves. To explore the underlying mechanism of this social phenomenon and to reveal its dynamic traits, we propose here a novel model which takes the effects of natural reversal parameter and opinion interaction on the individual’s view choice behavior into account based on the Hegselmann and Krause (HK) bounded confidence model. Experimental results show that the evolution of individual opinions is not only influenced by the interactions between neighboring individuals but also updated naturally due to individual factors themselves in the absence of interaction, which in turn proves that the proposed model can provide a reasonable description of the entire process of public opinion natural reversal under the Internet environment. Besides, the proportion of group opinion tendency, network topology, identification method, and the influence weight of opinion leader will play significant roles in this process, which further indicates our improved model is very robust and thus can provide some insightful evidence to understand the phenomena of opinion natural reversal.