IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02189758.html

Directed networks’ different link formation mechanisms causing degree distribution distinction

Author

Listed:
  • Stefan Behfar

    (BETA - Bureau d'Économie Théorique et Appliquée - INRA - Institut National de la Recherche Agronomique - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique)

  • Ekaterina Turkina

    (HEC Montréal - HEC Montréal)

  • Patrick Cohendet

    (HEC Montréal - HEC Montréal)

  • Thierry Burger-Helmchen

    (BETA - Bureau d'Économie Théorique et Appliquée - INRA - Institut National de la Recherche Agronomique - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique)

Abstract

Within undirected networks, scientists have shown much interest in presenting power-law features within complex networks. For instance, Barabási and Albert (1999) claimed that a common property of many large networks was that vertex connectivity follows scale-free power-law distribution, and in another study Barabási et al. (2002) showed power law evolution in the social network of scientific collaboration. At the same time, Jiang et al. (2011) discussed deviation from power-law distribution ; others indicated that size effect (Bagrow et al., 2008) ,information filtering mechanism (Mossa et al., 2002), and birth and death process (Shi et al., 2005) could account for this deviation. Within directed networks, many authors have considered that outlinks follow a similar mechanism of creation as inlinks' formation (Faloutsos et al., 1999 ; Krapivsky et al., 2001 ; Tanimoto, 2009) with link creation rate being the linear function of node degree, and a resulting power-law shape for both indegree and outdegree distribution. Some other authors have made an assumption that directed networks, such as scientific collaboration or citation, behave as undirected, resulting in a power-law degree distribution accordingly (Barabási et al., 2002). At the same time, we claim. Outlinks feature different degree distributions from inlinks ; where different link formation mechanisms cause the distribution distinctions, in/out degree distribution distinction holds for different levels of system decomposition ; therefore this distribution distinction is a property of directed networks. First, we emphasize in/out link formation mechanisms as causal factors for distinction between indegree and outdegree distributions (where this distinction has already been noticed in Barker et al. (2010) and Baxter et al. (2006)) within a sample network of OSS projects as well as Java software corpus as a network.Second, we analyze whether this distribution distinction holds for different levels of system decomposition : open-source-software (OSS) project–project dependency within a cluster, package–package dependency within a project and class–class dependency within a package. We conclude that indegree and outdegree dependencies do not lead to similar type of degree distributions, implying that indegree dependencies follow overall power-law distribution (or power-law with flat-top or exponential cut-off in some cases), while outdegree dependencies do not follow heavy-tailed distribution.

Suggested Citation

  • Stefan Behfar & Ekaterina Turkina & Patrick Cohendet & Thierry Burger-Helmchen, 2016. "Directed networks’ different link formation mechanisms causing degree distribution distinction," Post-Print hal-02189758, HAL.
  • Handle: RePEc:hal:journl:hal-02189758
    DOI: 10.1016/j.physa.2016.06.035
    Note: View the original document on HAL open archive server: https://hal.science/hal-02189758v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-02189758v1/document
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.physa.2016.06.035?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
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Bütün, Ertan & Kaya, Mehmet, 2019. "A pattern based supervised link prediction in directed complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1136-1145.

    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:hal:journl:hal-02189758. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.