IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02019489.html
   My bibliography  Save this paper

Explorer les réseaux à l’échelle de la triade : l’apport des modèles statistiques ERGM

Author

Listed:
  • Julien Brailly

    (IRISSO - Institut de Recherche Interdisciplinaire en Sciences Sociales - INRA - Institut National de la Recherche Agronomique - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Fabien Eloire

    (CLERSÉ - Centre Lillois d’Études et de Recherches Sociologiques et Économiques - UMR 8019 - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Guillaume Favre

    (LISST - Laboratoire Interdisciplinaire Solidarités, Sociétés, Territoires - EHESS - École des hautes études en sciences sociales - UT2J - Université Toulouse - Jean Jaurès - UT - Université de Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville - CNRS - Centre National de la Recherche Scientifique - INP - PURPAN - Ecole d'Ingénieurs de Purpan - Toulouse INP - Institut National Polytechnique (Toulouse) - UT - Université de Toulouse)

  • Alvaro Pina-Stranger

    (CSO - Centre de sociologie des organisations (Sciences Po, CNRS) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

Abstract

In contrast to conventional statistical analysis, statistical models for social networks must account for dependencies between observations. To address this issue, a specific class of models has been developed, Exponential Random Graph Models (ERGM). The basis for these models is the fundamental idea of triads, a longstanding concept within sociology, as seen in Simmel's work. This article aims to present for the first time in French ERGM's theoretical foundations, and reviews the usefulness of the triadic approach for exploring social processes. Using a case study of a business law firm, the ERGM estimation process is presented in detail, followed by a review of recent research using ERGM.

Suggested Citation

  • Julien Brailly & Fabien Eloire & Guillaume Favre & Alvaro Pina-Stranger, 2017. "Explorer les réseaux à l’échelle de la triade : l’apport des modèles statistiques ERGM," Post-Print hal-02019489, HAL.
  • Handle: RePEc:hal:journl:hal-02019489
    DOI: 10.3917/anso.171.0219
    Note: View the original document on HAL open archive server: https://hal.science/hal-02019489
    as

    Download full text from publisher

    File URL: https://hal.science/hal-02019489/document
    Download Restriction: no

    File URL: https://libkey.io/10.3917/anso.171.0219?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
    ---><---

    References listed on IDEAS

    as
    1. Favre, Guillaume, 2014. "Des rencontres dans la mondialisation : réseaux et apprentissages dans un salon de distribution de programmes de télévision en Afrique sub-saharienne," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14652 edited by Lazega, Emmanuel.
    2. Francesca Pallotti & Alessandro Lomi & Daniele Mascia, 2013. "From network ties to network structures: Exponential Random Graph Models of interorganizational relations," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1665-1685, April.
    3. Olaf N. Rank & Garry L. Robins & Philippa E. Pattison, 2010. "Structural Logic of Intraorganizational Networks," Organization Science, INFORMS, vol. 21(3), pages 745-764, June.
    4. repec:dau:papers:123456789/1821 is not listed on IDEAS
    5. Brailly, Julien, 2014. "Coopérer pour résister : interactions marchandes et réseaux multiniveaux dans un salon d'échanges de programmes de télévision en Europe Centrale et Orientale," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14874 edited by Lazega, Emmanuel & David, Albert.
    Full references (including those not matched with items on IDEAS)

    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. Julien Brailly & Fabien Eloire & Guillaume Favre & Alvaro Pina-Stranger, 2017. "Explorer les réseaux à l’échelle de la triade : l’apport des modèles statistiques ERGM," SciencePo Working papers Main hal-02019489, HAL.
    2. Alessandro Lomi & Dean Lusher & Philippa E. Pattison & Garry Robins, 2014. "The Focused Organization of Advice Relations: A Study in Boundary Crossing," Organization Science, INFORMS, vol. 25(2), pages 438-457, April.
    3. Eva Kesternich & Olaf Rank, 2022. "Beyond patient-sharing: Comparing physician- and patient-induced networks," Health Care Management Science, Springer, vol. 25(3), pages 498-514, September.
    4. Brennecke, Julia & Rank, Olaf, 2017. "The firm’s knowledge network and the transfer of advice among corporate inventors—A multilevel network study," Research Policy, Elsevier, vol. 46(4), pages 768-783.
    5. Christian Resch, 2017. "Networks in Assembly: Investigating Social Factors in Robotic Automation," IET Working Papers Series 01/2017, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology.
    6. Pierre Barbillon & Sophie Donnet & Emmanuel Lazega & Avner Bar-Hen, 2017. "Stochastic block models for multiplex networks: an application to a multilevel network of researchers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 295-314, January.
    7. Martina Pieperhoff, 2018. "Reziprozität in interorganisationalen Austauschbeziehungen - eine Typologisierung," ZfKE – Zeitschrift für KMU und Entrepreneurship, Duncker & Humblot, Berlin, vol. 66(4), pages 273-287.
    8. Filiposka, Sonja & Gajduk, Andrej & Dimitrova, Tamara & Kocarev, Ljupco, 2017. "Bridging online and offline social networks: Multiplex analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 825-836.
    9. Yongli Li & Guijie Zhang & Yuqiang Feng & Chong Wu, 2015. "An entropy-based social network community detecting method and its application to scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 1003-1017, January.
    10. Julia Brennecke & Irena Schierjott & Olaf Rank, 2016. "Informal Managerial Networks and Formal Firm Alliances," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 17(1), pages 103-125, April.
    11. Abbasiharofteh, Milad, 2020. "Endogenous effects and cluster transition: a conceptual framework for cluster policy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(12), pages 2508-2531.
    12. Yongli Li & Chong Wu & Zizheng Wang, 2015. "An information-theoretic approach for detecting communities in networks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1719-1733, July.
    13. Yuval Kalish & Amalya L. Oliver, 2022. "Reducing the cost of knowledge exchange in consortia: network analyses of multiple relations," The Journal of Technology Transfer, Springer, vol. 47(3), pages 775-803, June.
    14. Ashish Arora & Michelle Gittelman & Sarah Kaplan & John Lynch & Will Mitchell & Nicolaj Siggelkow & Ji Youn (Rose) Kim & Michael Howard & Emily Cox Pahnke & Warren Boeker, 2016. "Understanding network formation in strategy research: Exponential random graph models," Strategic Management Journal, Wiley Blackwell, vol. 37(1), pages 22-44, January.
    15. Manuel E. Sosa & Martin Gargiulo & Craig Rowles, 2015. "Can Informal Communication Networks Disrupt Coordination in New Product Development Projects?," Organization Science, INFORMS, vol. 26(4), pages 1059-1078, August.
    16. Steve Phelps, 2016. "An Empirical Game-Theoretic Analysis of the Dynamics of Cooperation in Small Groups," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(2), pages 1-4.
    17. Brennecke, Julia & Sofka, Wolfgang & Wang, Peng & Rank, Olaf N., 2021. "How the organizational design of R&D units affects individual search intensity – A network study," Research Policy, Elsevier, vol. 50(5).

    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-02019489. 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: 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.