IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v90y2017i7d10.1140_epjb_e2017-80031-x.html
   My bibliography  Save this article

Fractality and degree correlations in scale-free networks

Author

Listed:
  • Yuka Fujiki

    (Hokkaido University)

  • Shogo Mizutaka

    (School of Statistical Thinking, The Institute of Statistical Mathematics)

  • Kousuke Yakubo

    (Hokkaido University)

Abstract

Fractal scale-free networks are empirically known to exhibit disassortative degree mixing. It is, however, not obvious whether a negative degree correlation between nearest neighbor nodes makes a scale-free network fractal. Here we examine the possibility that disassortativity in complex networks is the origin of fractality. To this end, maximally disassortative (MD) networks are prepared by rewiring edges while keeping the degree sequence of an initial uncorrelated scale-free network. We show that there are many MD networks with different topologies if the degree sequence is the same with that of the (u,v)-flower but most of them are not fractal. These results demonstrate that disassortativity does not cause the fractal property of networks. In addition, we suggest that fractality of scale-free networks requires a long-range repulsive correlation, in the sense of the shortest path distance, in similar degrees.

Suggested Citation

  • Yuka Fujiki & Shogo Mizutaka & Kousuke Yakubo, 2017. "Fractality and degree correlations in scale-free networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(7), pages 1-9, July.
    • Handle: RePEc:spr:eurphb:v:90:y:2017:i:7:d:10.1140_epjb_e2017-80031-x
    DOI: 10.1140/epjb/e2017-80031-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/e2017-80031-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1140/epjb/e2017-80031-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Statistical and Nonlinear Physics;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eurphb:v:90:y:2017:i:7:d:10.1140_epjb_e2017-80031-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.