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Community detection is a fundamental problem in network analysis with many methods available to estimate communities.
An information flow model for conflict and fission in small groups
W. W. Zachary · 1977
Earlier work this paper cites.
Stochastic blockmodels: first steps
P. W. Holland, K. B. Laskey, and S. Leinhardt · 1983
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Zeta functions of finite graphs and representations of p-adic groups
K. Hashimoto · 1989
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The Ihara-Selberg zeta function of a tree lattice
H. Bass · 1992
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Matrix Analysis
R. Bhatia · 1996
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Spectral partitioning of random graphs
McSherry · 2001
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Community structure in social and biological networks
M. Girvan and M. E. J. Newman · 2002
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The bottlenose dolphin community of doubtful sound features a large propor- tion of long-lasting associations. can geographic isola- tion explain this unique trait?
D. Lusseau, K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, and S. M. Dawson · 2003
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Finding and evaluating community structure in networks
M. E. J. Newman and M. Girvan · 2004
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The political blogosphere and the 2004 US election
L. A. Adamic and N. Glance · 2005
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Finding community structure in networks using the eigenvectors of matrices
M. E. J. Newman · 2006
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Modularity and community structure in networks
M. E. J. Newman · 2006
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Mixed membership stochastic blockmodels
E. M. Airoldi, D. M. Blei, S. E. Fienberg, and E. P. Xing · 2008
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A mixture model for random graphs
J. Daudin, F. Picard, and S. Robin · 2008
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Random discrete matrices
V. Vu · 2008
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A nonparametric view of network models and Newman-Girvan and other modularities
P. J. Bickel and A. Chen · 2009
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B. Karrer and M. E. J. Newman · 2011
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Spectral clustering and the high-dimensional stochastic block model
K. Rohe, S. Chatterjee, and B. Yu · 2011
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Spectral clustering of graphs with general degrees in the extended planted partition model
K. Chaudhuri, F. Chung, and A. Tsiatas · 2012
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Variational bayesian inference and complexity control for stochastic block models
P. Latouche, E. Birmelé, and C. Ambroise · 2012
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Network cross-validation by edge sampling
T. Li, E. Levina, and J. Zhu · 2016
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Spectral radii of sparse random matrices
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Concentration and regularization of random graphs
C. M. Le, E. Levina, and R. Vershynin · 2017
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Efficient method for estimating the number of communities in a network
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How many communities are there?
D. F. Saldana, Y. Yu, and Y. Feng · 2017
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E. Mossel, J. Neeman, and A. Sly · 2012
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Pseudo-likelihood methods for community detection in large sparse networks
A. A. Amini, A. Chen, P. J. Bickel, and E. Levina · 2013
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Hypothesis testing for automated community detection in networks
P. Bickel and P. Sarkar · 2013
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Spectral redemption in clustering sparse networks
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Parsimonious module inference in large networks
T. P. Peixoto · 2013
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Community detection thresholds and the weak ramanujan property
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Reconstruction and estimation in the planted partition model
E. Mossel, J. Neeman, and A. Sly · 2014
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K. Wang and P. M. Wood · 2017
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Likelihood-based model selection for stochastic block models
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Non-backtracking spectrum of random graphs: community detection and non-regular Ramanujan graphs
C. Bordenave, M. Lelarge, and L. Massoulié · 2018
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Network cross-validation for determining the number of communities in network data
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Determining the number of communities in degree-corrected stochastic block models
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A proof of the block model threshold conjecture
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A simple SVD algorithm for finding hidden partitions
V. Vu · 2018
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Provable estimation of the number of blocks in block models
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Corrected bayesian information criterion for stochastic block models
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