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How Homophily Affects the Speed of Learning and Best Response Dynamics


Benjamin Golub


Stanford Graduate School of Business

Matthew O. Jackson


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

February 4, 2012

FEEM Working Paper No. 35.2009

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.

Number of Pages in PDF File: 60

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

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Date posted: August 8, 2009 ; Last revised: August 29, 2012

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: http://ssrn.com/abstract=1443787 or http://dx.doi.org/10.2139/ssrn.1443787

Contact Information

Benjamin Golub (Contact Author)
Stanford Graduate School of Business ( email )
518 Memorial 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
Feedback to SSRN (Beta)


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