English

A Stochastic Model for the Evolution of the Web

Disordered Systems and Neural Networks 2007-05-23 v2

Abstract

Recently several authors have proposed stochastic models of the growth of the Web graph that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the ``rich get richer'' phenomenon. However, these models fail to explain several distributions arising from empirical results, due to the fact that the predicted exponent is not consistent with the data. To address this problem, we extend the evolutionary model of the Web graph by including a non-preferential component, and we view the stochastic process in terms of an urn transfer model. By making this extension, we can now explain a wider variety of empirically discovered power-law distributions provided the exponent is greater than two. These include: the distribution of incoming links, the distribution of outgoing links, the distribution of pages in a Web site and the distribution of visitors to a Web site. A by-product of our results is a formal proof of the convergence of the standard stochastic model (first proposed by Simon).

Keywords

Cite

@article{arxiv.cond-mat/0110016,
  title  = {A Stochastic Model for the Evolution of the Web},
  author = {Mark Levene and Trevor Fenner and George Loizou and Richard Wheeldon},
  journal= {arXiv preprint arXiv:cond-mat/0110016},
  year   = {2007}
}

Comments

16 pages

R2 v1 2026-07-22T10:28:03.869Z