IDEAS home Printed from https://ideas.repec.org/a/cup/netsci/v3y2015i02p183-195_00.html
   My bibliography  Save this article

A clustering coefficient for complete weighted networks

Author

Listed:
  • MCASSEY, MICHAEL P.
  • BIJMA, FETSJE

Abstract

The clustering coefficient is typically used as a measure of the prevalence of node clusters in a network. Various definitions for this measure have been proposed for the cases of networks having weighted edges which may or not be directed. However, these techniques consistently assume that only a subset of all possible edges is present in the network, whereas there are weighted networks of interest in which all possible edges are present, that is, complete weighted networks. For this situation, the concept of clustering is redefined, and computational techniques are presented for computing an associated clustering coefficient for complete weighted undirected or directed networks. The performance of this new definition is compared with that of current clustering definitions when extended to complete weighted networks.

Suggested Citation

  • Mcassey, Michael P. & Bijma, Fetsje, 2015. "A clustering coefficient for complete weighted networks," Network Science, Cambridge University Press, vol. 3(2), pages 183-195, June.
    • Handle: RePEc:cup:netsci:v:3:y:2015:i:02:p:183-195_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S2050124214000265/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. João Amador & Sónia Cabral & Rossana Mastrandrea & Franco Ruzzenenti, 2018. "Who’s Who in Global Value Chains? A Weighted Network Approach," Open Economies Review, Springer, vol. 29(5), pages 1039-1059, November.
    2. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    3. Roy Cerqueti & Gian Paolo Clemente & Rosanna Grassi, 2019. "A Network-Based Measure of the Socio-Economic Roots of the Migration Flows," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 187-204, November.
    4. Herteliu, Claudiu & Levantesi, Susanna & Rotundo, Giulia, 2021. "Network analysis of pension funds investments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 579(C).
    5. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    6. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    7. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    8. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    9. Sun, Hang, 2016. "Crisis-Contingent Dynamics of Connectedness: An SVAR-Spatial-Network “Tripod” Model with Thresholds," Research Memorandum 032, Maastricht University, Graduate School of Business and Economics (GSBE).
    10. Leonidov, Andrey & Serebryannikova, Ekaterina, 2019. "Dynamical topology of highly aggregated input–output networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 234-252.

    More about this item

    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:cup:netsci:v:3:y:2015:i:02:p:183-195_00. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/nws .

    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.