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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 - Comue de Toulouse - Communauté d'universités et établissements 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) - Comue de Toulouse - Communauté d'universités et établissements 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," SciencePo Working papers Main hal-02019489, HAL.
    • Handle: RePEc:hal:spmain:hal-02019489
    DOI: 10.3917/anso.171.0219
    Note: View the original document on HAL open archive server: https://hal.science/hal-02019489v1
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    References listed on IDEAS

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