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Identifying Community Structures from Network Data via Maximum Likelihood Methods

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Author Info

  • Copic Jernej

    ()
    (UCLA)

  • Jackson Matthew O.

    ()
    (Stanford University and Santa Fe Institute)

  • Kirman Alan

    ()
    (GREQAM)

Abstract

Networks of social and economic interactions are often influenced by unobserved structures among the nodes. Based on a simple model of how an unobserved community structure generates networks of interactions, we axiomatize a method of detecting the latent community structures from network data. The method is based on maximum likelihood estimation.

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Bibliographic Info

Article provided by De Gruyter in its journal The B.E. Journal of Theoretical Economics.

Volume (Year): 9 (2009)
Issue (Month): 1 (September)
Pages: 1-40

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Handle: RePEc:bpj:bejtec:v:9:y:2009:i:1:n:30

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Web page: http://www.degruyter.com

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Cited by:
  1. Ben R. Craig & Goetz von Peter, 2009. "Interbank tiering and money center banks," Working Paper 0912, Federal Reserve Bank of Cleveland.
  2. Dev, Pritha, 2010. "Identity and Fragmentation in Networks," MPRA Paper 21632, University Library of Munich, Germany.

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