Directed closure measures for networks with reciprocity

The study of triangles in graphs is a standard tool in network analysis, leading to measures such as the \emph{transitivity}, i.e., the fraction of paths of length $2$ that participate in triangles. Real-world networks are often directed, and it can be difficult to "measure" this network structure meaningfully. We propose a collection of \emph{directed closure values} for measuring triangles in directed graphs in a way that is analogous to transitivity in an undirected graph. Our study of these values reveals much information about directed triadic closure. For instance, we immediately see that reciprocal edges have a high propensity to participate in triangles. We also observe striking similarities between the triadic closure patterns of different web and social networks. We perform mathematical and empirical analysis showing that directed configuration models that preserve reciprocity cannot capture the triadic closure patterns of real networks.

[1]  S. Leinhardt,et al.  The Structure of Positive Interpersonal Relations in Small Groups. , 1967 .

[2]  J. Kurths,et al.  Reciprocity of networks with degree correlations and arbitrary degree sequences. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

[4]  Sergei Vassilvitskii,et al.  Counting triangles and the curse of the last reducer , 2011, WWW.

[5]  Diego Garlaschelli,et al.  Triadic motifs and dyadic self-organization in the World Trade Network , 2012, IWSOS.

[6]  S. Grossberg,et al.  Psychological Review , 2003 .

[7]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[8]  John Skvoretz,et al.  Biased net theory: Approximations, simulations and observations , 1990 .

[9]  Tamara G. Kolda,et al.  A scalable null model for directed graphs matching all degree distributions: In, out, and reciprocal , 2012, 2013 IEEE 2nd Network Science Workshop (NSW).

[10]  Ah Reum Kang,et al.  Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game , 2012, PloS one.

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

[12]  F. Heider Attitudes and cognitive organization. , 1946, The Journal of psychology.

[13]  W. Hoeffding Probability Inequalities for sums of Bounded Random Variables , 1963 .

[14]  Krishna P. Gummadi,et al.  Growth of the flickr social network , 2008, WOSN '08.

[15]  Jure Leskovec,et al.  Signed networks in social media , 2010, CHI.

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

[17]  Giorgio Fagiolo,et al.  Null models of economic networks: the case of the world trade web , 2011, 1112.2895.

[18]  Francesco Picciolo,et al.  Reciprocity of weighted networks , 2012, Scientific Reports.

[19]  S E Ahnert,et al.  Clustering signatures classify directed networks. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  John Skvoretz,et al.  Advances in biased net theory: definitions, derivations, and estimations , 2004, Soc. Networks.

[21]  G. Fagiolo Clustering in complex directed networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  A. Martin-Löf,et al.  Generating Simple Random Graphs with Prescribed Degree Distribution , 2006, 1509.06985.

[23]  VoLUME Xxxix,et al.  THE AMERICAN JOURNAL OF SOCIOLOGY , 2010 .

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

[25]  Tamara G. Kolda,et al.  Degree relations of triangles in real-world networks and graph models , 2012, CIKM.

[26]  P. Holland,et al.  A Method for Detecting Structure in Sociometric Data , 1970, American Journal of Sociology.

[27]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[28]  L. Christophorou Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.

[29]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[30]  Katherine Faust,et al.  A puzzle concerning triads in social networks: Graph constraints and the triad census , 2010, Soc. Networks.

[31]  V. Zlatic,et al.  Influence of reciprocal edges on degree distribution and degree correlations. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  Diego Garlaschelli,et al.  Patterns of link reciprocity in directed networks. , 2004, Physical review letters.

[33]  Dorothea Wagner,et al.  Finding, Counting and Listing All Triangles in Large Graphs, an Experimental Study , 2005, WEA.

[34]  Michael Szell,et al.  Measuring social dynamics in a massive multiplayer online game , 2009, Soc. Networks.

[35]  Katherine Faust,et al.  Comparing Social Networks: Size, Density, and Local Structure , 2006 .

[36]  F. Harary,et al.  STRUCTURAL BALANCE: A GENERALIZATION OF HEIDER'S THEORY1 , 1977 .

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

[38]  Tamara G. Kolda,et al.  Degree Relations of Triangles in Real-world Networks and Models , 2012, arXiv.org.

[39]  Silvio Lattanzi,et al.  On compressing social networks , 2009, KDD.

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

[41]  Tamara G. Kolda,et al.  Triadic Measures on Graphs: The Power of Wedge Sampling , 2012, SDM.

[42]  Tamara G. Kolda,et al.  Community structure and scale-free collections of Erdös-Rényi graphs , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[43]  G. Homans The human group , 1952 .

[44]  Robert Cole,et al.  Computer Communications , 1982, Springer New York.

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

[46]  Michael Szell,et al.  Multirelational organization of large-scale social networks in an online world , 2010, Proceedings of the National Academy of Sciences.

[47]  Jonathan Cohen,et al.  Graph Twiddling in a MapReduce World , 2009, Computing in Science & Engineering.

[48]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[49]  R. Burt Structural Holes and Good Ideas1 , 2004, American Journal of Sociology.

[50]  W. Marsden I and J , 2012 .

[51]  D. Garlaschelli,et al.  Multispecies grand-canonical models for networks with reciprocity. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[52]  Sergio Gómez,et al.  Detecting communities of triangles in complex networks using spectral optimization , 2010, Comput. Commun..

[53]  Tamara G. Kolda,et al.  A scalable directed graph model with reciprocal edges , 2012, ArXiv.

[54]  Norishige Chiba,et al.  Arboricity and Subgraph Listing Algorithms , 1985, SIAM J. Comput..

[55]  Jörg Reichardt,et al.  Motifs in Triadic Random Graphs based on Steiner Triple Systems , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  Stephanie Forrest,et al.  Email networks and the spread of computer viruses. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.