Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities

Andrea Lancichinetti and Santo Fortunato
Phys. Rev. E 80, 016118 – Published 31 July 2009

Abstract

Many complex networks display a mesoscopic structure with groups of nodes sharing many links with the other nodes in their group and comparatively few with nodes of different groups. This feature is known as community structure and encodes precious information about the organization and the function of the nodes. Many algorithms have been proposed but it is not yet clear how they should be tested. Recently we have proposed a general class of undirected and unweighted benchmark graphs, with heterogeneous distributions of node degree and community size. An increasing attention has been recently devoted to develop algorithms able to consider the direction and the weight of the links, which require suitable benchmark graphs for testing. In this paper we extend the basic ideas behind our previous benchmark to generate directed and weighted networks with built-in community structure. We also consider the possibility that nodes belong to more communities, a feature occurring in real systems, such as social networks. As a practical application, we show how modularity optimization performs on our benchmark.

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  • Received 24 April 2009

DOI:https://doi.org/10.1103/PhysRevE.80.016118

©2009 American Physical Society

Authors & Affiliations

Andrea Lancichinetti and Santo Fortunato

  • Complex Networks Lagrange Laboratory (CNLL), Institute for Scientific Interchange (ISI), Viale S. Severo 65, 10133 Torino, Italy

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Vol. 80, Iss. 1 — July 2009

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