E. M. Airoldi, D. M. Blei, S. E. Fienberg, and E. P. Xing, Mixed membership stochastic blockmodels, The Journal of Machine Learning Research, vol.9, pp.1981-2014, 2008.

R. Albert and A. L. Barabási, Statistical mechanics of complex networks, Reviews of Modern Physics, vol.74, issue.1, pp.47-97, 2002.
DOI : 10.1103/RevModPhys.74.47

C. Ambroise, G. Grasseau, M. Hoebeke, P. Latouche, V. Miele et al., The mixer R package, 2010.

P. J. Bickel and A. Chen, A nonparametric view of network models and Newman???Girvan and other modularities, Proceedings of the National Academy of Sciences, vol.106, issue.50, pp.21068-21073, 2009.
DOI : 10.1073/pnas.0907096106

C. Biernacki, G. Celeux, and G. Govaert, Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models, Computational Statistics & Data Analysis, vol.41, issue.3-4, pp.561-575, 2003.
DOI : 10.1016/S0167-9473(02)00163-9

J. A. Bilmes, A gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models, International Computer Science Institute, vol.4, p.126, 1998.

C. M. Bishop, Pattern recognition and machine learning, 2006.

A. Celisse, J. Daudin, and L. Pierre, Consistency of maximum-likelihood and variational estimators in the stochastic block model, Electronic Journal of Statistics, vol.6, issue.0, pp.1847-1899, 2012.
DOI : 10.1214/12-EJS729
URL : https://hal.archives-ouvertes.fr/hal-00593644

J. Daudin, F. Picard, and S. Robin, A mixture model for random graphs, Statistics and Computing, vol.4, issue.2, pp.173-183, 2008.
DOI : 10.1007/s11222-007-9046-7
URL : https://hal.archives-ouvertes.fr/inria-00070186

S. E. Fienberg and S. S. Wasserman, Categorical Data Analysis of Single Sociometric Relations, Sociological Methodology, vol.12, pp.156-192, 1981.
DOI : 10.2307/270741

O. Frank and F. Harary, Cluster Inference by using Transitivity Indices in Empirical Graphs, Journal of the American Statistical Association, vol.39, issue.380, pp.835-840, 1982.
DOI : 10.1080/01621459.1973.10481342

M. Girvan and M. E. Newman, Community structure in social and biological networks, Proceedings of the National Academy of Sciences, p.7821, 2002.
DOI : 10.1073/pnas.122653799

A. Goldenberg, A. X. Zheng, and S. E. Fienberg, A survey of statistical network models, 2010.

M. S. Handcock, A. E. Raftery, and J. M. Tantrum, Model-based clustering for social networks, Journal of the Royal Statistical Society: Series A (Statistics in Society), vol.6, issue.2, pp.301-354, 2007.
DOI : 10.1111/j.1467-9574.2005.00283.x

J. M. Hofman and C. H. Wiggins, Bayesian approach to network modularity. Physical review letters, p.258701, 2008.

P. W. Holland and S. Leinhardt, An Exponential Family of Probability Distributions for Directed Graphs, Journal of the American Statistical Association, vol.1, issue.373, pp.33-65, 1981.
DOI : 10.1080/01621459.1981.10477598

H. Jeffreys, An Invariant Form for the Prior Probability in Estimation Problems, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.186, issue.1007, pp.453-461, 1946.
DOI : 10.1098/rspa.1946.0056

C. Kemp, J. B. Tenenbaum, T. L. Griffiths, T. Yamada, and N. Ueda, Learning systems of concepts with an infinite relational model, Proceedings of the National Conference on Artificial Intelligence, p.381, 2006.

P. Latouche, E. Birmelé, and C. Ambroise, Advances in Data Analysis Data Handling and Business Intelligence Bayesian methods for graph clustering 229-239, 2009.

P. Latouche, E. Birmelé, and C. Ambroise, Overlapping stochastic block models with application to the French political blogosphere, The Annals of Applied Statistics, vol.5, issue.1, pp.309-336, 2011.
DOI : 10.1214/10-AOAS382SUPP
URL : https://hal.archives-ouvertes.fr/hal-00624538

P. Latouche, E. Birmelé, and C. Ambroise, Variational Bayesian inference and complexity control for stochastic block models, Statistical Modelling, vol.12, issue.1, pp.93-115, 2012.
DOI : 10.1177/1471082X1001200105
URL : https://hal.archives-ouvertes.fr/hal-00624536

M. Mariadassou and C. Matias, Convergence of the groups posterior distribution in latent or stochastic block models, Bernoulli, vol.21, issue.1, 2013.
DOI : 10.3150/13-BEJ579
URL : https://hal.archives-ouvertes.fr/hal-01174515

R. Milo, S. Shen-orr, S. Itzkovitz, D. Kashtan, D. Chklovskii et al., Network Motifs: Simple Building Blocks of Complex Networks, Science, vol.298, issue.5594, pp.824-827, 2002.
DOI : 10.1126/science.298.5594.824

J. L. Moreno, Who shall survive?: A new approach to the problem of human interrelations, 1934.
DOI : 10.1037/10648-000

K. Nowicki and T. A. Snijders, Estimation and Prediction for Stochastic Blockstructures, Journal of the American Statistical Association, vol.96, issue.455, pp.1077-1087, 2001.
DOI : 10.1198/016214501753208735

G. Palla, I. Derenyi, I. Farkas, and T. Vicsek, Uncovering the overlapping community structure of complex networks in nature and society, Nature, vol.387, issue.7043, pp.814-818, 2005.
DOI : 10.1038/nature03248

W. M. Rand, Objective Criteria for the Evaluation of Clustering Methods, Journal of the American Statistical Association, vol.15, issue.336, pp.846-850, 1971.
DOI : 10.1080/01621459.1963.10500845

M. Salter-townshend, A. White, I. Gollini, and T. B. Murphy, Review of statistical network analysis: models, algorithms, and software, Statistical Analysis and Data Mining, vol.4, issue.4, pp.243-264, 2012.
DOI : 10.1002/sam.11146

T. A. Snijders and K. Nowicki, Estimation and Prediction for Stochastic Blockmodels for Graphs with Latent Block Structure, Journal of Classification, vol.14, issue.1, pp.75-100, 1997.
DOI : 10.1007/s003579900004

H. A. Soufiani and E. M. Airoldi, Graphlet decomposition of a weighted network Arxiv preprint arXiv, pp.1203-2821, 2012.

N. Villa, F. Rossi, and Q. D. Truong, Mining a medieval social network by kernel SOM and related methods, Arxiv preprint, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00278196

Y. J. Wang and G. Y. Wong, Stochastic Blockmodels for Directed Graphs, Journal of the American Statistical Association, vol.4, issue.397, pp.8-19, 1987.
DOI : 10.1080/01621459.1987.10478406

H. C. White, S. A. Boorman, and R. L. Breiger, Social Structure from Multiple Networks. I. Blockmodels of Roles and Positions, American Journal of Sociology, vol.81, issue.4, pp.730-780, 1976.
DOI : 10.1086/226141

E. P. Xing, W. Fu, and L. Song, A state-space mixed membership blockmodel for dynamic network tomography, The Annals of Applied Statistics, vol.4, issue.2, pp.535-566, 2010.
DOI : 10.1214/09-AOAS311