Author:
Traag Vincent A.,Šubelj Lovro
Abstract
AbstractMany networks exhibit some community structure. There exists a wide variety of approaches to detect communities in networks, each offering different interpretations and associated algorithms. For large networks, there is the additional requirement of speed. In this context, the so-called label propagation algorithm (LPA) was proposed, which runs in near-linear time. In partitions uncovered by LPA, each node is ensured to have most links to its assigned community. We here propose a fast variant of LPA (FLPA) that is based on processing a queue of nodes whose neighbourhood recently changed. We test FLPA exhaustively on benchmark networks and empirical networks, finding that it can run up to 700 times faster than LPA. In partitions found by FLPA, we prove that each node is again guaranteed to have most links to its assigned community. Our results show that FLPA is generally preferable to LPA.
Funder
Javna Agencija za Raziskovalno Dejavnost RS
Publisher
Springer Science and Business Media LLC
Reference40 articles.
1. Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, 026113 (2004).
2. Peixoto, T. P. Bayesian stochastic blockmodeling. In Doreian, P., Batagelj, V. & Ferligoj, A. (eds.) Advances in Network Clustering and Blockmodeling, Computational and Quantitative Social Science, 281–324 (Wiley, New York, 2020), 1st edn.
3. Rosvall, M. & Bergstrom, C. T. An information-theoretic framework for resolving community structure in complex networks. P. Natl. Acad. Sci. USA 104, 7327–7331 (2007).
4. Rosvall, M. & Bergstrom, C. T. Maps of random walks on complex networks reveal community structure. Proc. Natl. Acad. Sci. U. S. A. 105, 1118–1123 (2008).
5. Clauset, A., Newman, M. E. J. & Moore, C. Finding community structure in very large networks. Physi. Rev. E 70, 066111 (2004).
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献