Model selection and hypothesis testing for large-scale network models with overlapping groups

Modeling a network with too many parameters is likely to lead to overfitting. The minimum description length principle is used to reliably model networks and robustly differentiate models on the basis of confidence levels.

[1]  Raj Rao Nadakuditi,et al.  Graph spectra and the detectability of community structure in networks , 2012, Physical review letters.

[2]  Andrew Sears,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 2002, CHI 2002.

[3]  Jorma Rissanen,et al.  Information and Complexity in Statistical Modeling , 2006, ITW.

[4]  P. Holme.  Core-periphery organization of complex networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  S. Wasserman,et al.  Building stochastic blockmodels , 1992 .

[6]  Karan P. Singh,et al.  Theoretical Biology and Medical Modelling , 2007 .

[7]  Jure Leskovec,et al.  Discovering social circles in ego networks , 2012, ACM Trans. Knowl. Discov. Data.

[8]  Martin Rosvall,et al.  Memory in network flows and its effects on spreading dynamics and community detection , 2013, Nature Communications.

[9]  Ernesto Estrada,et al.  Journal of Complex Networks: Quo Vadis? , 2013, J. Complex Networks.

[10]  Jure Leskovec,et al.  Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters , 2008, Internet Math..

[11]  Christos Faloutsos,et al.  Kronecker Graphs: An Approach to Modeling Networks , 2008, J. Mach. Learn. Res..

[12]  Tiago P. Peixoto,et al.  Trust Transitivity in Social Networks , 2010, PloS one.

[13]  Aaron Clauset,et al.  Learning Latent Block Structure in Weighted Networks , 2014, J. Complex Networks.

[14]  Cristopher Moore,et al.  Phase transition in the detection of modules in sparse networks , 2011, Physical review letters.

[15]  Mark E. J. Newman,et al.  Spectral methods for network community detection and graph partitioning , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  P. Marais.  Ieee Transactions on Visualization and Computer Graphics 1 Warp Sculpting , 2022 .

[17]  Sean R. Collins,et al.  Toward a Comprehensive Atlas of the Physical Interactome of Saccharomyces cerevisiae*S , 2007, Molecular & Cellular Proteomics.

[18]  Edoardo M. Airoldi,et al.  Mixed Membership Stochastic Blockmodels , 2007, NIPS.

[19]  S. Wasserman,et al.  Blockmodels: Interpretation and evaluation , 1992 .

[20]  Mark E. J. Newman,et al.  Friendship networks and social status , 2012, Network Science.

[21]  Mason A. Porter,et al.  Multilayer networks , 2013, J. Complex Networks.

[22]  Kathryn B. Laskey,et al.  Stochastic blockmodels: First steps , 1983 .

[23]  Tiago P. Peixoto.  The entropy of stochastic blockmodel ensembles , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  Ulrik Brandes,et al.  What is network science? , 2013, Network Science.

[25]  P. Latouche,et al.  Model Selection in Overlapping Stochastic Block Models , 2014, 1405.2722.

[26]  Ulrik Brandes,et al.  Social Networks , 2013, Handbook of Graph Drawing and Visualization.

[27]  R. Guimerà,et al.  Functional cartography of complex metabolic networks , 2005, Nature.

[28]  D. Lusseau,et al.  The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations , 2003, Behavioral Ecology and Sociobiology.

[29]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[30]  F. Radicchi,et al.  Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[31]  October I.  Physical Review Letters , 2022 .

[32]  M. Newman.  Communities, modules and large-scale structure in networks , 2011, Nature Physics.

[33]  Daniel B. Larremore,et al.  Efficiently inferring community structure in bipartite networks , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[34]  Donald E. Knuth,et al.  The Stanford GraphBase - a platform for combinatorial computing , 1993 .

[35]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[36]  J. Brown.  Behavioral Ecology and Sociobiology , 2019, Encyclopedia of Animal Behavior.

[37]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[38]  Sandhya Rani,et al.  Human Protein Reference Database—2009 update , 2008, Nucleic Acids Res..

[39]  Tiago P. Peixoto.  Hierarchical block structures and high-resolution model selection in large networks , 2013, ArXiv.

[40]  Danny Holten,et al.  Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data , 2006, IEEE Transactions on Visualization and Computer Graphics.

[41]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[42]  David M Blei,et al.  Efficient discovery of overlapping communities in massive networks , 2013, Proceedings of the National Academy of Sciences.

[43]  A. Barabasi,et al.  High-Quality Binary Protein Interaction Map of the Yeast Interactome Network , 2008, Science.

[44]  Elchanan Mossel,et al.  Spectral redemption in clustering sparse networks , 2013, Proceedings of the National Academy of Sciences.

[45]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[46]  L. M. M.-T..  Theory of Probability , 1929, Nature.

[47]  Isabelle Herlin,et al.  Computer Vision – ECCV 2012 , 2012, Lecture Notes in Computer Science.

[48]  H. J. Mclaughlin,et al.  Learn , 2002 .

[49]  J. Herskowitz,et al.  Proceedings of the National Academy of Sciences, USA , 1996, Current Biology.

[50]  Peter D. Hoff,et al.  Latent Space Approaches to Social Network Analysis , 2002 .

[51]  Dunja Mladenic,et al.  Proceedings of the 3rd international workshop on Link discovery , 2005, KDD 2005.

[52]  M. M. Meyer,et al.  Statistical Analysis of Multiple Sociometric Relations. , 1985 .

[53]  T. Ideker,et al.  Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae , 2006, Journal of biology.

[54]  Journal of Chemical Physics , 1932, Nature.

[55]  Mark E. J. Newman,et al.  An efficient and principled method for detecting communities in networks , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  Andrea Lancichinetti,et al.  Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.

[57]  O. William.  Journal Of The American Statistical Association V-28 , 1932 .

[58]  P. Grünwald.  The Minimum Description Length Principle (Adaptive Computation and Machine Learning) , 2007 .

[59]  Philip S. Yu,et al.  Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics , 2012, KDD 2012.

[60]  Mark E. J. Newman,et al.  Stochastic blockmodels and community structure in networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[61]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[62]  K. Pearson.  Biometrika , 1902, The American Naturalist.

[63]  Martin Rosvall,et al.  Compression of flow can reveal overlapping modular organization in networks , 2011, ArXiv.

[64]  O. Bagasra,et al.  Proceedings of the National Academy of Sciences , 1914, Science.

[65]  Tiago P. Peixoto.  Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[66]  Roger Guimerà,et al.  Missing and spurious interactions and the reconstruction of complex networks , 2009, Proceedings of the National Academy of Sciences.

[67]  Mark E. J. Newman,et al.  Community detection and graph partitioning , 2013, ArXiv.

[68]  Juliana Freire,et al.  Proceedings of the 19th international conference on World wide web , 2010, WWW 2010.

[69]  Chid Apte,et al.  Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011 , 2011, KDD.

[70]  HighWire Press,et al.  Molecular & cellular proteomics , 2002 .

[71]  Harry Eugene Stanley,et al.  Catastrophic cascade of failures in interdependent networks , 2009, Nature.

[72]  V. Colizza,et al.  Metapopulation epidemic models with heterogeneous mixing and travel behaviour , 2014, Theoretical Biology and Medical Modelling.

[73]  Matthias Zwicker,et al.  Ieee Transactions on Visualization and Computer Graphics Ewa Splatting , 2002 .

[74]  Andrea Lancichinetti,et al.  Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[75]  Tiago P Peixoto,et al.  Parsimonious module inference in large networks. , 2012, Physical review letters.

[76]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[77]  Julio Collado-Vides,et al.  RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more , 2012, Nucleic Acids Res..

[78]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[79]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[80]  Alastair J. Gill,et al.  In Proceedings of the 26th annual conference of the , 2004 .

[81]  St'ephane Robin,et al.  Uncovering latent structure in valued graphs: A variational approach , 2010, 1011.1813.

[82]  Sune Lehmann,et al.  Link communities reveal multiscale complexity in networks , 2009, Nature.

[83]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[84]  R. Rosenfeld.  Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[85]  M. Newman,et al.  Robustness of community structure in networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[86]  Martin Rosvall,et al.  An information-theoretic framework for resolving community structure in complex networks , 2007, Proceedings of the National Academy of Sciences.

[87]  Andrea Lancichinetti,et al.  Detecting the overlapping and hierarchical community structure in complex networks , 2008, 0802.1218.

[88]  A. Arenas,et al.  Community analysis in social networks , 2004 .

[89]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[90]  G. Hong,et al.  Nucleic Acids Research , 2015, Nucleic Acids Research.

[91]  Christos Faloutsos,et al.  Graph evolution: Densification and shrinking diameters , 2006, TKDD.

[92]  A. Barabasi,et al.  The human disease network , 2007, Proceedings of the National Academy of Sciences.

[93]  Scott P. Robertson,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 1991 .

[94]  László Lovász,et al.  Multifractal network generator , 2010, Proceedings of the National Academy of Sciences.

[95]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[96]  M. Newman,et al.  Hierarchical structure and the prediction of missing links in networks , 2008, Nature.

[97]  G. Bianconi.  Entropy of network ensembles. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[98]  Cristopher Moore,et al.  Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[99]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[100]  Cristopher Moore,et al.  Model selection for degree-corrected block models , 2012, Journal of statistical mechanics.

[101]  Luciano da Fontoura Costa,et al.  Journal of Complex Networks , 2013 .

[102]  John Mylopoulos,et al.  The Semantic Web - ISWC 2003 , 2003, Lecture Notes in Computer Science.