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

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dc.creatorZheng, Dafang
dc.creatorHui, P. M.
dc.creatorJohnson, N. F.
dc.date2001-05-24
dc.date.accessioned2026-07-07T02:41:31Z
dc.date.available2026-07-07T02:41:31Z
dc.descriptionWe 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.
dc.identifierhttps://arxiv.org/abs/cond-mat/0105474
dc.identifierhttp://arxiv.org/abs/cond-mat/0105474
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/17773
dc.subjectDisordered Systems and Neural Networks
dc.titleNon-universal scaling in a model of information transmission and herd behavior
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