Abstract

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 textsf {NP}-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 textsf {FPT} 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.

Highlights

  • The increasing availability of large network datasets has led to great interest in techniques to discover network structure

  • We demonstrate that Modularity, parameterised by treewidth, is unlikely to belong to FPT: we prove that the problem is W[1]-hard even when parameterised simultaneously by the pathwidth of G and the size of a minimum feedback vertex set for G

  • We identify a number of structural restrictions on the input graph that allow us to compute the maximum modularity of a graph, or a good approximation to this quantity, efficiently

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Summary

Introduction

The increasing availability of large network datasets has led to great interest in techniques to discover network structure. The crucial difference between the two problems is that the input to Equitable Connected Partition includes the required number of parts, whereas Modularity requires us to maximise over all possible partition sizes; if we restrict to partitions with a specified parts, it is no longer necessarily true that a partition maximising the modularity must induce connected subgraphs. This difference makes reductions between the two problems non-trivial

The Modularity Function
Notation and Definitions
Parameterisation by Vertex Cover Number
Parameterisation by Treewidth
Parameterisation by Max Leaf Number
Hardness results
Conclusions and Open Problems
Full Text
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