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Scale-free networks are rare. Public Deposited

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https://scholar.colorado.edu/concern/articles/d791sg80r
Abstract
  • Real-world networks are often claimed to be scale free, meaning that the fraction of nodes with degree k follows a power law k, a pattern with broad implications for the structure and dynamics of complex systems. However, the universality of scale-free networks remains controversial. Here, we organize different definitions of scale-free networks and construct a severe test of their empirical prevalence using state-of-the-art statistical tools applied to nearly 1000 social, biological, technological, transportation, and information networks. Across these networks, we find robust evidence that strongly scale-free structure is empirically rare, while for most networks, log-normal distributions fit the data as well or better than power laws. Furthermore, social networks are at best weakly scale free, while a handful of technological and biological networks appear strongly scale free. These findings highlight the structural diversity of real-world networks and the need for new theoretical explanations of these non-scale-free patterns.

Creator
Date Issued
  • 2019-03-04
Academic Affiliation
Journal Title
Journal Issue/Number
  • 1
Journal Volume
  • 10
File Extent
  • 1017-1017
Subject
Last Modified
  • 2020-02-17
Identifier
  • PubMed ID: 30833554
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DOI
ISSN
  • 2041-1723
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