How Homophily Affects the Speed of Learning and Best Response Dynamics

60 Pages Posted: 8 Aug 2009 Last revised: 29 Aug 2012

See all articles by Benjamin Golub

Benjamin Golub

Stanford Graduate School of Business

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute; Canadian Institute for Advanced Research (CIFAR)

Date Written: February 4, 2012

Abstract

We examine how the speed of learning and best-response processes depends on homophily: the tendency of agents to associate disproportionately with those having similar traits. When agents’ beliefs or behaviors are developed by averaging what they see among their neighbors, then convergence to a consensus is slowed by the presence of homophily, but is not influenced by network density (in contrast to other network processes that depend on shortest paths). In deriving these results, we propose a new, general measure of homophily based on the relative frequencies of interactions among different groups. An application to communication in a society before a vote shows how the time it takes for the vote to correctly aggregate information depends on the homophily and the initial information distribution.

Keywords: Networks, Learning, Diffusion, Homophily, Friendships, Social Networks, Random Graphs, Mixing Time, Convergence, Speed of Learning, Speed of Convergence

JEL Classification: D83, D85, I21, J15, Z13

Suggested Citation

Golub, Benjamin and Jackson, Matthew O., How Homophily Affects the Speed of Learning and Best Response Dynamics (February 4, 2012). FEEM Working Paper No. 35.2009. Available at SSRN: https://ssrn.com/abstract=1443787 or http://dx.doi.org/10.2139/ssrn.1443787

Benjamin Golub (Contact Author)

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Matthew O. Jackson

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

Canadian Institute for Advanced Research (CIFAR) ( email )

180 Dundas Street West, Suite 1400
Toronto, Ontario
Canada

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