Public Opinion Evolution Based on Complex Networks

Abstract

Abstract The Sznajd model of sociophysics can describe the mechanism of making a decision in a closed community. The Complex Agent Networks (CAN) model is studied, based on the adaptability, autonomy and activity of the individuals, as well as the complex interactions of individuals in an open community for probing into evolution of the public opinion. With the help of the theory of complex adaptive systems and the methods of complex networks, the structure of agents, the dynamic networks scenarios and the evolutionary process of the agents are described. The simulation results of CAN model show that all individuals cannot reach a final consensus through mutual consultations when the small world networks rewiring probability p is less than a specified threshold. But when the rewiring probability p is larger than the given threshold, all individuals will eventually come to a finial consensus, and that the rewiring probability p increases, whereas the time of emergence of the public opinion will be significantly reduced. It is quite obvious that in real community the mass media and many other mechanisms have an effect on the evolutionary process of the public opinion.