  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.
