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Statistical Models for Social Networks

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Data Analysis, Classification, and Related Methods

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Abstract

Recent developments in statistical models for social networks reflect an increasing theoretical focus in the social and behavioral sciences on the interdependence of social actors in dynamic, network-based social settings (e.g., Abbott, 1997; White, 1992, 1995). As a result, a growing importance has been accorded the problem of modeling the dynamic and complex interdependencies among network ties and the actions of the individuals whom they link. Included in this problem is the identification of cohesive subgroups, or classifications of the individuals. The early focus of statistical network modeling on the mathematical and statistical properties of Bernoulli and dyad-independent random graph distributions has now been replaced by efforts to construct theoretically and empirically plausible parametric models for structural network phenomena and their changes over time.

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Authors and Affiliations

  1. Department of Psychology and Department of Statistics,Beckman Institute for Advanced Science and Technology, University of Illinois, 603 East Daniel Street, Champaign, Illinois, 61820, USA

    Stanley Wasserman

  2. School of Behavioural Science, Department of Psychology, University of Melbourne, Parkville, Victoria, 3052, Australia

    Philippa Pattison

Authors
  1. Stanley Wasserman
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  2. Philippa Pattison
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Editor information

Editors and Affiliations

  1. University of Groningen Heymans Institute (PA), Grote Kruisstraat 2/1, NL-9712 TS, Groningen, The Netherlands

    Henk A. L. Kiers

  2. Facultés Universitaires Notre-Dame de la Paix, University of Namur, Rempart de la Vierge, 8, B-5000, Namur, Belgium

    Jean-Paul Rasson (Directeur du Department de Mathématique) (Directeur du Department de Mathématique)

  3. Data Theory Group Department of Education, Leiden University, P.O. Box 9555, NL-2300 RB, Leiden, The Netherlands

    Patrick J. F. Groenen

  4. Lehrstuhl für Wirtschaftsinformatik III Schloß, University of Mannheim, D-68131, Mannheim, Germany

    Martin Schader

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© 2000 Springer-Verlag Berlin · Heidelberg

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Wasserman, S., Pattison, P. (2000). Statistical Models for Social Networks. In: Kiers, H.A.L., Rasson, JP., Groenen, P.J.F., Schader, M. (eds) Data Analysis, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59789-3_46

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  • DOI: https://doi.org/10.1007/978-3-642-59789-3_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67521-1

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