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Identifying Community Structures from Network Data via Maximum Likelihood Methods

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Author Info
Jernej Copic (UCLA)
Matthew O. Jackson (Stanford University and Santa Fe Institute)
Alan Kirman (GREQAM)

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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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File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1523&context=bejte
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Publisher Info
Article provided by Berkeley Electronic Press in its journal The B.E. Journal of Theoretical Economics.

Volume (Year): 9 (2009)
Issue (Month): 1 ()
Pages:
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Handle: RePEc:bpj:bejtec:v:9:y:2009:i:1:n:30

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Web page: http://www.bepress.com/bejte

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Related research
Keywords: networks; communities; community structures; maximum likelihood; social networks;

Find related papers by JEL classification:
D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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This page was last updated on 2009-11-21.

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