Non-universal scaling in a model of information transmission and herd behavior

Abstract

We present a generalized dynamical model describing the sharing of information, and corresponding herd behavior, in a population based on the recent model proposed by Eguiluz and Zimmermann. By introducing a size-dependent probability for dissociation of a cluster, we show that the exponent characterizing the distribution of cluster sizes becomes model-dependent and non-universal. The resulting system, which provides a simplified model of a financial market, yields power law behavior with an easily tunable exponent.