Opinion spreading and consensus formation on complex networks:

We study a model of opinion spreading and consensus formation in a population on complex networks. Given a static network structure, the individuals can diffuse on it when two neighboring individuals’ opinions are beyond the “bounded confidence” ε. This is the case that arises in political situations while the opinions of voters can be adapted promptly after communication. The model is governed by the following two rules. At each time step, each individual can exchange their opinions with their neighbors if the difference of their opinions is smaller than ε; otherwise, one can move to an vacancy location if permitted. The distribution of opinions over the population evolves towards either a consensus that all individuals share the same opinion or polarization and fragmentation state. The statistical properties of this final state vary considerably as the model parameters change. It is shown that, when the dispersal abilities of the individuals are considered, the bounded confidence which is required to attain consensus can be remarkably decrease.