Long-Run Integration in Social Networks

38 Pages Posted: 13 Jan 2011

See all articles by Sergio Currarini

Sergio Currarini

University of Leicester - Department of Economics

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute

Paolo Pin

Dipartimento di Economia Politica, Università degli Studi di Siena

Date Written: January 12, 2011


We study network formation where nodes are born sequentially and form links with previously born nodes. Connections are formed through a combination of random meetings and through search, as in Jackson and Rogers (2007). A newborn's random meetings of existing nodes are type-dependent and the newborn's search is then by meeting the neighbors of the randomly met nodes. We study 'long-run integration', which requires that as a node ages sufficiently, the type distribution of the nodes connected to it approaches the overall type - distribution of the population. We show that long-run integration occurs if and only if the search part of the network formation process is unbiased, and that eventually the search process dominates in terms of the new links that an older node obtains. Integration, however, only occurs for sufficiently old nodes, and the aggregate type-distribution of connections in the network still reflects the bias of the random process. We illustrate the model with data on scientific citations in physics journals.

Keywords: social networks, homophily, integration, segregation, network formation, citation networks, networks

JEL Classification: D85, C72, L14, Z13, J15, J71

Suggested Citation

Currarini, Sergio and Jackson, Matthew O. and Pin, Paolo, Long-Run Integration in Social Networks (January 12, 2011). Available at SSRN: https://ssrn.com/abstract=1739439 or http://dx.doi.org/10.2139/ssrn.1739439

Sergio Currarini

University of Leicester - Department of Economics ( email )

School of Business
Leicester LE1 7RH, Leicestershire LE1 7RH
United Kingdom

Matthew O. Jackson (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
1-650-723-3544 (Phone)

HOME PAGE: http://www.stanford.edu/~jacksonm

Santa Fe Institute

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Paolo Pin

Dipartimento di Economia Politica, Università degli Studi di Siena ( email )

Piazza San Francesco 8
Siena, I53100

HOME PAGE: http://www.econ-pol.unisi.it/paolopin/

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