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Convergence to global consensus in opinion dynamics under a nonlinear voter model (1008.0901v2)
Published 5 Aug 2010 in stat.AP, nlin.AO, and physics.soc-ph
Abstract: We propose a nonlinear voter model to study the emergence of global consensus in opinion dynamics. In our model, agent $i$ agrees with one of binary opinions with the probability that is a power function of the number of agents holding this opinion among agent $i$ and its nearest neighbors, where an adjustable parameter $\alpha$ controls the effect of herd behavior on consensus. We find that there exists an optimal value of $\alpha$ leading to the fastest consensus for lattices, random graphs, small-world networks and scale-free networks. Qualitative insights are obtained by examining the spatiotemporal evolution of the opinion clusters.