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Network Structure and the Speed of Learning Measuring Homophily Based on its Consequences

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  • Benjamin Golub
  • Matthew O. Jackson

Abstract

Homophily is the tendency of people to associate relatively more with those who are similar to them than with those who are not. In Golub and Jackson (2010a), we introduced degree-weighted homophily (DWH), a new measure of this phenomenon, and showed that it gives a lower bound on the time it takes for a certain natural best-reply or learning process operating in a social network to converge. Here we show that, in important settings, the DWH convergence bound does substantially better than previous bounds based on the Cheeger inequality. We also develop a new complementary upper bound on convergence time, tightening the relationship between DWH and updating processes on networks. In doing so, we suggest that DWH is a natural homophily measure because it tightly tracks a key consequence of homophily - namely, slowdowns in updating processes.

Suggested Citation

  • Benjamin Golub & Matthew O. Jackson, 2012. "Network Structure and the Speed of Learning Measuring Homophily Based on its Consequences," Annals of Economics and Statistics, GENES, issue 107-108, pages 33-48.
  • Handle: RePEc:adr:anecst:y:2012:i:107-108:p:33-48
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    Cited by:

    1. Proto, Eugenio & Rustichini, Aldo & Sofianos, Andis, 2014. "Higher Intelligence Groups Have Higher Cooperation Rates in the Repeated Prisoner's Dilemma," IZA Discussion Papers 8499, Institute for the Study of Labor (IZA).
    2. Proto, Eugenio & Sgroi, Daniel, 2017. "Biased beliefs and imperfect information," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 186-202.
    3. Susanna Gallani, 2015. "Through the Grapevine: Network Effects on the Design of Executive Compensation Contracts," Harvard Business School Working Papers 16-019, Harvard Business School, revised Dec 2016.

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