Opinion dynamics in networks with bounded confidence and influence

We study a discrete-time model of opinion dynamics in which each agent has its own confidence and influence radius. We investigate the influence of heterogeneity in confidence/influence distribution on the behavior of the network. We consider three cases: 1) each agent has the same confidence and influence radius; 2) each agent´s confidence radius is inversely proportional to its influence radius; 3) each agent´s confidence radius is not related to its influence radius. We find that heterogeneity does not always promote consensus, and there is an optimal heterogeneity so that the size of the largest consensus cluster reaches maximum.