The Parameterised Complexity of Computing the Maximum Modularity of a Graph

The maximum modularity of a graph is a parameter widely used to describe the level of clustering or community structure in a network. Determining the maximum modularity of a graph is known to be NP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf {NP}$$\end{document}-complete in general, and in practice a range of heuristics are used to construct partitions of the vertex-set which give lower bounds on the maximum modularity but without any guarantee on how close these bounds are to the true maximum. In this paper we investigate the parameterised complexity of determining the maximum modularity with respect to various standard structural parameterisations of the input graph G. We show that the problem belongs to FPT\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\textsf {FPT}$$\end{document} when parameterised by the size of a minimum vertex cover for G, and is solvable in polynomial time whenever the treewidth or max leaf number of G is bounded by some fixed constant; we also obtain an FPT algorithm, parameterised by treewidth, to compute any constant-factor approximation to the maximum modularity. On the other hand we show that the problem is W[1]-hard (and hence unlikely to admit an FPT algorithm) when parameterised simultaneously by pathwidth and the size of a minimum feedback vertex set.

[1]  Michael R. Fellows,et al.  Fundamentals of Parameterized Complexity , 2013 .

[2]  Ton Kloks Treewidth, Computations and Approximations , 1994, Lecture Notes in Computer Science.

[3]  Liudmila Ostroumova,et al.  Modularity in several random graph models , 2017, Electron. Notes Discret. Math..

[4]  Santo Fortunato,et al.  Limits of modularity maximization in community detection , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Ulrik Brandes,et al.  On Modularity Clustering , 2008, IEEE Transactions on Knowledge and Data Engineering.

[6]  Michal Pilipczuk,et al.  Parameterized Algorithms , 2015, Springer International Publishing.

[7]  Hans L. Bodlaender A linear time algorithm for finding tree-decompositions of small treewidth , 1993, STOC '93.

[8]  Laurent Viennot,et al.  Asymptotic Modularity of Some Graph Classes , 2011, ISAAC.

[9]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[10]  Bhaskar DasGupta,et al.  On the complexity of Newman's community finding approach for biological and social networks , 2011, J. Comput. Syst. Sci..

[11]  Colin McDiarmid,et al.  Modularity of Erdős‐Rényi random graphs , 2018, AofA.

[12]  James P. Bagrow,et al.  Communities and bottlenecks: trees and treelike networks have high modularity. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Fiona Skerman,et al.  Modularity of networks , 2015 .

[14]  Michael R. Fellows,et al.  What Makes Equitable Connected Partition Easy , 2009, IWPEC.

[15]  Tomomi Matsui,et al.  Additive Approximation Algorithms for Modularity Maximization , 2016, ISAAC.

[16]  Xiang Li,et al.  Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits , 2015, 2015 IEEE International Conference on Data Mining.

[17]  Santo Fortunato,et al.  Community detection in networks: A user guide , 2016, ArXiv.

[18]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Colin McDiarmid,et al.  Modularity of regular and treelike graphs , 2018, J. Complex Networks.

[20]  Mason A. Porter,et al.  Communities in Networks , 2009, ArXiv.

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

[22]  My T. Thai,et al.  Community Detection in Scale-Free Networks: Approximation Algorithms for Maximizing Modularity , 2013, IEEE Journal on Selected Areas in Communications.

[23]  Daniel Lokshtanov,et al.  Parameterized Integer Quadratic Programming: Variables and Coefficients , 2015, ArXiv.

[24]  Michael R. Fellows,et al.  FPT is P-Time Extremal Structure I , 2005, ACiD.

[25]  My T. Thai,et al.  Finding Community Structure with Performance Guarantees in Scale-Free Networks , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.