Homophily and long-run integration in social networks
AbstractWe 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 nodesʼ neighborhoods approaches the global type-distribution, provided that the network-based search is unbiased. However, younger nodesʼ 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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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Theory.
Volume (Year): 147 (2012)
Issue (Month): 5 ()
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Web page: http://www.elsevier.com/locate/inca/622869
Network formation; Social networks; Homophily; Integration; Degree distribution; Citations;
Find related papers by JEL classification:
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
- A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
- Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Social and Economic Stratification
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- Lafond, Francois, 2012. "Learning and the structure of citation networks," UNU-MERIT Working Paper Series 071, United Nations University, Maastricht Economic and social Research and training centre on Innovation and Technology.
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