Non-universal scaling in a model of information transmission and herd behavior
Disordered Systems and Neural Networks
2007-05-23 v1
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.
Keywords
Cite
@article{arxiv.cond-mat/0105474,
title = {Non-universal scaling in a model of information transmission and herd behavior},
author = {Dafang Zheng and P. M. Hui and N. F. Johnson},
journal= {arXiv preprint arXiv:cond-mat/0105474},
year = {2007}
}