We present numerical simulations of a model of social influence, where the opinion of each agent is represented by a binary vector. Agents adjust their opinions as a result of random encounters, whenever the difference between opinions is below a given threshold. Evolution leads to a steady state, which highly depends on the threshold and a convergence parameter of the model. We analyze the transition between clustered and homogeneous steady states. Results of the cases of complete mixing and small-world networks are compared.
@article{arxiv.cond-mat/0307623,
title = {Vector opinion dynamics in a model for social influence},
author = {M. F. Laguna and Guillermo Abramson and Damian H. Zanette},
journal= {arXiv preprint arXiv:cond-mat/0307623},
year = {2009}
}
Comments
Latex file, 14 pages and 11 figures, Accepted in Physica A