Network decomposition into fixed points of degree peeling

Degree peeling is used to study complex networks. It is a decomposition of the network into vertex groups of increasing minimum degree. However, the peeling value of a vertex is non-local in this context since it relies on the number of connections the vertex has to groups above it. We explore a different way to decompose a network into edge layers such that the local peeling value of the vertices on each layer does not depend on their non-local connections with the other layers. This corresponds to the decomposition of a graph into subgraphs that are invariant with respect to degree peeling, i.e., they are fixed points. We introduce a general method to partition the edges of an arbitrary graph into fixed points of degree peeling called the iterative edge core decomposition. Information from this decomposition is used to formulate a novel notion of vertex diversity based on Shannon’s entropy. We illustrate the usefulness of this decomposition on a variety of social networks including weighted graphs. Our method can be used as a preprocessing step for community detection and graph visualization.

[1]  Romain Bourqui,et al.  Comparing Multilevel Clustering Methods on Weighted Graphs: The Case of Worldwide Air Passenger Traf , 2013 .

[2]  Lada A. Adamic,et al.  The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.

[3]  P. Erdos,et al.  On the evolution of random graphs , 1984 .

[4]  B. Bollobás The evolution of random graphs , 1984 .

[5]  Francesco De Pellegrini,et al.  General , 1895, The Social History of Alcohol Review.

[6]  Charu C. Aggarwal,et al.  Graph Clustering , 2010, Encyclopedia of Machine Learning and Data Mining.

[7]  P. Erdos,et al.  On chromatic number of graphs and set-systems , 1966 .

[8]  Tim Roughgarden,et al.  Preventing Unraveling in Social Networks: The Anchored k-Core Problem , 2012, SIAM J. Discret. Math..

[9]  Ulrik Brandes,et al.  Drawing the AS Graph in 2.5 Dimensions , 2004, GD.

[10]  Stephen B. Seidman,et al.  Network structure and minimum degree , 1983 .

[11]  Guy Melançon,et al.  Continental integration in multilevel approach of world air transportation (2000-2004) , 2008 .

[12]  Alessandro Vespignani,et al.  Large scale networks fingerprinting and visualization using the k-core decomposition , 2005, NIPS.

[13]  David Eppstein,et al.  Listing All Maximal Cliques in Sparse Graphs in Near-optimal Time , 2010, Exact Complexity of NP-hard Problems.

[14]  Satu Elisa Schaeffer,et al.  Graph Clustering , 2017, Encyclopedia of Machine Learning and Data Mining.

[15]  Yuval Shavitt,et al.  A model of Internet topology using k-shell decomposition , 2007, Proceedings of the National Academy of Sciences.

[16]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[17]  Michael T. Goodrich,et al.  External-Memory Network Analysis Algorithms for Naturally Sparse Graphs , 2011, ESA.

[18]  D. R. Lick,et al.  k-Degenerate Graphs , 1970, Canadian Journal of Mathematics.

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

[20]  David Eppstein,et al.  Listing All Maximal Cliques in Large Sparse Real-World Graphs , 2011, JEAL.

[21]  G. Szekeres,et al.  An inequality for the chromatic number of a graph , 1968 .

[22]  P. Erdos,et al.  On chromatic number of graphs and set-systems , 1966 .

[23]  Joel H. Spencer,et al.  Sudden Emergence of a Giantk-Core in a Random Graph , 1996, J. Comb. Theory, Ser. B.

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

[25]  Dorothea Wagner,et al.  Enumerating and Generating Labeled k-degenerate Graphs , 2010, ANALCO.

[26]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[27]  Dimitrios M. Thilikos,et al.  Evaluating Cooperation in Communities with the k-Core Structure , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[28]  Vladimir Batagelj,et al.  An O(m) Algorithm for Cores Decomposition of Networks , 2003, ArXiv.

[29]  Charles F. Hockett,et al.  A mathematical theory of communication , 1948, MOCO.

[30]  Dimitrios M. Thilikos,et al.  D-cores: measuring collaboration of directed graphs based on degeneracy , 2011, Knowledge and Information Systems.

[31]  B. Arnold Majorization and the Lorenz Order: A Brief Introduction , 1987 .

[32]  A. Rbnyi ON THE EVOLUTION OF RANDOM GRAPHS , 2001 .

[33]  Eli V. Olinick,et al.  The use of sparsest cuts to reveal the hierarchical community structure of social networks , 2008, Soc. Networks.

[34]  Ann Lieberman The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations , 2005 .

[35]  Andrew Parker,et al.  The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations , 2004 .