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The B.E. Journal of Theoretical Economics

Editor-in-Chief: Schipper, Burkhard

Ed. by Fong, Yuk-fai / Peeters, Ronald / Puzzello , Daniela / Rivas, Javier / Wenzelburger, Jan

IMPACT FACTOR 2018: 0.173
5-year IMPACT FACTOR: 0.248

CiteScore 2018: 0.24

SCImago Journal Rank (SJR) 2018: 0.163
Source Normalized Impact per Paper (SNIP) 2018: 0.186

Mathematical Citation Quotient (MCQ) 2018: 0.08

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Identifying Community Structures from Network Data via Maximum Likelihood Methods

Jernej Copic / Matthew O. Jackson / Alan Kirman
Published Online: 2009-09-27 | DOI: https://doi.org/10.2202/1935-1704.1523

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.

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

About the article

Published Online: 2009-09-27

Citation Information: The B.E. Journal of Theoretical Economics, Volume 9, Issue 1, ISSN (Online) 1935-1704, DOI: https://doi.org/10.2202/1935-1704.1523.

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