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How Homophily Affects Learning and Diffusion in Networks

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  • Benjamin Golub

    (Stanford University)

  • Matthew O. Jackson

    (Stanford University)

Abstract

We examine how three different communication processes operating through social networks are affected by homophily - the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are broadcast or sent via shortest paths; only connection density matters. In contrast, homophily substantially slows learning based on repeated averaging of neighbors' information and Markovian diffusion processes such as the Google random surfer model. Indeed, the latter processes are strongly affected by homophily but completely independent of connection density, provided this density exceeds a low threshold. We obtain these results by establishing new results on the spectra of large random graphs and relating the spectra to homophily. We conclude by checking the theoretical predictions using observed high school friendship networks from the Adolescent Health dataset.

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Bibliographic Info

Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2009.35.

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Date of creation: May 2009
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Handle: RePEc:fem:femwpa:2009.35

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Related research

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

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  1. Peter M. Demarzo & Dimitri Vayanos & Jeffrey Zwiebel, 2003. "Persuasion Bias, Social Influence, And Unidimensional Opinions," The Quarterly Journal of Economics, MIT Press, vol. 118(3), pages 909-968, August.
  2. A. Banerjee & Drew Fudenberg, 2010. "Word-of-Mouth Communication and Social Learning," Levine's Working Paper Archive 425, David K. Levine.
  3. Ellison, Glenn, 2000. "Basins of Attraction, Long-Run Stochastic Stability, and the Speed of Step-by-Step Evolution," Review of Economic Studies, Wiley Blackwell, vol. 67(1), pages 17-45, January.
  4. Bala, Venkatesh & Goyal, Sanjeev, 1998. "Learning from Neighbours," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 595-621, July.
  5. Abhijit Banerjee & Drew Fudenberg, 2010. "Word of Mouth Learning," Levine's Working Paper Archive 723, David K. Levine.
  6. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
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