A Method for Detecting Structure in Sociometric Data

  • Holland P
  • Leinhardt S
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Abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. The authors focus on developing standardized measures for models of structure in interpersonal relations. A theorem is presented which yields expectations and variances for measures based on triads. Random models for these measures are discussed and the procedure is carried out for a model of a partial order. This model contains as special cases a number of previously suggested models, including the structural balance model of Cartwright and Harary, Davis's clustering model, and the ranked-clusters model of Davis and Leinhardt. In an illustrative example, eight sociograms are analyzed and the general model is compared with the special case of ranked clusters.

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Holland, P. W., & Leinhardt, S. (1970). A Method for Detecting Structure in Sociometric Data. American Journal of Sociology, 76(3), 492–513. https://doi.org/10.1086/224954

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