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arXiv · 1201.4564

Homophily and Long-Run Integration in Social Networks

Yann Bramoullé·Sergio Currarini·Matthew O. Jackson·Paolo Pin·Brian W. Rogers
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Abstract

We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is "long-run integration," whereby the composition of types in sufficiently old nodes' neighborhoods approaches the global type distribution, provided that the network-based search is unbiased. However, younger nodes' connections still reflect the biased meetings process. We derive the type-based degree distributions and group-level homophily patterns when there are two types and location-based biases. Finally, we illustrate aspects of the model with an empirical application to data on citations in physics journals.

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Yann Bramoullé, Sergio Currarini, Matthew O. Jackson, Paolo Pin, Brian W. Rogers. 2012-04-07. Homophily and Long-Run Integration in Social Networks. https://arxiv.org/abs/1201.4564

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