The Dynamics and Formation of Extremism and Non-Extremism Opinion Communities in Complex Social Networks

Extremism commonly exists in social networks. Studying the dynamics and evolution of extremism and non-extremism opinions in social networks is of significant importance. Extremists are paranoid. It is typically not easy for them to accept other people's opinions. In this paper, we extend the well-known Deffuant model to resemble the real-life observations that extremists tend to be less tolerant of different opinions. We also evaluate the impacts such differences in tolerance may make on system opinion evolution. Further, to better understand the effects of different people's different willingness to compro-mise in order to achieve consensus-making, we introduce two communication logics, named unidirectional consensus-making and bi-directionality consensus-making, where opinion change for consensus-making can or cannot happen on single-side, respectively. It is found that bi-directionality consensus-making leads to a more stable formation of the opinion communities in the final state, while unidirectional consensus-making, typically sourced from good willingness to achieve consensus as it is, may actually lead to less stable results and give extremism opinions a better chance to prevail. Simulations have been carried out on different cases with different tolerance ranges, and some interesting observations have been made.