Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v462y2016icp479-491.html
   My bibliography  Save this article

Directed networks’ different link formation mechanisms causing degree distribution distinction

Author

Listed:
  • Behfar, Stefan Kambiz
  • Turkina, Ekaterina
  • Cohendet, Patrick
  • Burger-Helmchen, Thierry

Abstract

Within undirected networks, scientists have shown much interest in presenting power-law features. For instance, Barabási and Albert (1999) claimed that a common property of many large networks is 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’ (Faloutsos et al., 1999; Krapivsky et al., 2001; Tanimoto, 2009) with link creation rate being the linear function of node degree, resulting in a 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 (1) Outlinks feature different degree distributions than inlinks; where different link formation mechanisms cause the distribution distinctions, (2) in/outdegree distribution distinction holds for different levels of system decomposition; therefore this distribution distinction is a property of directed networks. First, we emphasize in/outlink 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

  • Behfar, Stefan Kambiz & Turkina, Ekaterina & Cohendet, Patrick & Burger-Helmchen, Thierry, 2016. "Directed networks’ different link formation mechanisms causing degree distribution distinction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 479-491.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:479-491
    DOI: 10.1016/j.physa.2016.06.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843711630303X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    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
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. J. Jiang & R. Wang & Q. A. Wang, 2011. "Network model of deviation from power-law distribution in complex network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 79(1), pages 29-33, January.
    2. Ergün, G. & Rodgers, G.J., 2002. "Growing random networks with fitness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 261-272.
    3. James Ma & Daniel Zeng & Huimin Zhao, 2012. "Modeling the growth of complex software function dependency networks," Information Systems Frontiers, Springer, vol. 14(2), pages 301-315, April.
    4. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    5. Xin-Jian Xu & Liu-Ming Zhang & Li-Jie Zhang, 2010. "Mutual Selection In Network Evolution: The Role Of The Intrinsic Fitness," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 129-135.
    6. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    7. James P. Bagrow & Jie Sun & Daniel ben-Avraham, 2007. "Phase transition in the rich-get-richer mechanism due to finite-size effects," Papers 0712.2220, arXiv.org, revised May 2008.
    8. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
    Full references (including those not matched with items on IDEAS)

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhengzheng Pan, 2012. "Opinions and Networks: How Do They Effect Each Other," Computational Economics, Springer;Society for Computational Economics, vol. 39(2), pages 157-171, February.
    2. Laurent Bergé & Iris Wanzenböck & Thomas Scherngell, 2015. "Centrality of regions in R&D networks: Conceptual clarifications and a new measure," Cahiers du GREThA (2007-2019) 2015-31, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    3. Carayol, Nicolas & Bergé, Laurent & Cassi, Lorenzo & Roux, Pascale, 2019. "Unintended triadic closure in social networks: The strategic formation of research collaborations between French inventors," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 218-238.
    4. Mehmet N. Aydin & N. Ziya Perdahci, 0. "Dynamic network analysis of online interactive platform," Information Systems Frontiers, Springer, vol. 0, pages 1-12.
    5. Mehmet N. Aydin & N. Ziya Perdahci, 2019. "Dynamic network analysis of online interactive platform," Information Systems Frontiers, Springer, vol. 21(2), pages 229-240, April.
    6. Antoni Rubí-Barceló, 2012. "Core/periphery scientific collaboration networks among very similar researchers," Theory and Decision, Springer, vol. 72(4), pages 463-483, April.
    7. Han, Rui-Qi & Li, Ming-Xia & Chen, Wei & Zhou, Wei-Xing & Stanley, H. Eugene, 2019. "Structural properties of statistically validated empirical information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 747-756.
    8. Anthony Edo & Nicolas Jacquemet & Constantine Yannelis, 2019. "Language skills and homophilous hiring discrimination: Evidence from gender and racially differentiated applications," Review of Economics of the Household, Springer, vol. 17(1), pages 349-376, March.
    9. Eunae Yoo & Elliot Rabinovich & Bin Gu, 2020. "The Growth of Follower Networks on Social Media Platforms for Humanitarian Operations," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2696-2715, December.
    10. Laurent R. Bergé, 2017. "Network proximity in the geography of research collaboration," Papers in Regional Science, Wiley Blackwell, vol. 96(4), pages 785-815, November.
    11. Lemarchand, Guillermo A., 2012. "The long-term dynamics of co-authorship scientific networks: Iberoamerican countries (1973–2010)," Research Policy, Elsevier, vol. 41(2), pages 291-305.
    12. Ann Bostrom & Ragnar E. Löfstedt, 2003. "Communicating Risk: Wireless and Hardwired," Risk Analysis, John Wiley & Sons, vol. 23(2), pages 241-248, April.
    13. Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano & Luca Mastrogiacomo, 2012. "The success-index: an alternative approach to the h-index for evaluating an individual’s research output," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 621-641, September.
    14. Lilian Cervo Cabrera & Carlos Eduardo Caldarelli & Marcia Regina Gabardo Camara, 2020. "Mapping collaboration in international coffee certification research," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2597-2618, September.
    15. de Oliveira, Thaiane Moreira & de Albuquerque, Sofia & Toth, Janderson Pereira & Bello, Debora Zava, 2018. "International cooperation networks of the BRICS bloc," SocArXiv b6x43, Center for Open Science.
    16. Marcus Berliant & Axel H. Watanabe, 2018. "A scale‐free transportation network explains the city‐size distribution," Quantitative Economics, Econometric Society, vol. 9(3), pages 1419-1451, November.
    17. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    18. Roland Pongou & Roberto Serrano, 2009. "A dynamic theory of fidelity networks with an application to the spread of HIV/AIDS," Working Papers 2009-03, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    19. Gabrielle Demange, 2012. "On the influence of a ranking system," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 39(2), pages 431-455, July.
    20. Mundt, Philipp, 2021. "The formation of input–output architecture: Evidence from the European Union," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 89-104.

    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:eee:phsmap:v:462:y:2016:i:c:p:479-491. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.