Preferential urn model and nongrowing complex networks

Jun Ohkubo, Muneki Yasuda, Kazuyuki Tanaka

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

A preferential urn model, which is based on the concept "the rich get richer," is proposed. From a relationship between a nongrowing model for complex networks and the preferential urn model in regard to degree distributions, it is revealed that a fitness parameter in the nongrowing model is interpreted as an inverse local temperature in the preferential urn model. Furthermore, it is clarified that the preferential urn model with randomness generates a fat-tailed occupation distribution; the concept of the local temperature enables us to understand the fat-tailed occupation distribution intuitively. Since the preferential urn model is a simple stochastic model, it can be applied to research on not only the nongrowing complex networks, but also many other fields such as econophysics and social sciences.

Original languageEnglish
Article number065104
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume72
Issue number6
DOIs
Publication statusPublished - 2005 Dec 1

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Mathematical Physics

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