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Leaving us in tiers: can homophily be used to generate tiering effects?

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Abstract

Substantial evidence indicates that our social networks are divided into tiers in which people have a few very close social support group, a larger set of friends, and a much larger number of relatively distant acquaintances. Because homophily—the principle that like seeks like—has been suggested as a mechanism by which people interact, it may also provide a mechanism that generates such frequencies and distributions. However, our multi-agent simulation tool, Construct, suggests that a slight supplement to a knowledge homophily model—the inclusion of several highly salient personal facts that are infrequently shared—can more successfully lead to the tiering behavior often observed in human networks than a simplistic homophily model. Our findings imply that homophily on both general and personal facts is necessary in order to achieve realistic frequencies of interaction and distributions of interaction partners. Implications of the model are discussed, and recommendations are provided for simulation designers seeking to use homophily models to explain human interaction patterns.

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Authors and Affiliations

  1. Computation, Organization and Society Program, School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA

    Brian R. Hirshman, Jesse St. Charles & Kathleen M. Carley

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  1. Brian R. Hirshman
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  2. Jesse St. Charles
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  3. Kathleen M. Carley
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Correspondence to Brian R. Hirshman.

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Hirshman, B.R., St. Charles, J. & Carley, K.M. Leaving us in tiers: can homophily be used to generate tiering effects?. Comput Math Organ Theory 17, 318–343 (2011). https://doi.org/10.1007/s10588-011-9088-4

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