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From Louvain to Leiden: guaranteeing well-connected communities

Scientific Reports · 2019 · Vol. 9(1) · pp. 5233–5233
V. A. TraagL. WaltmanN. J. van Eck

Abstract

Community detection is often used to understand the structure of large and complex networks. One of the most popular algorithms for uncovering community structure is the so-called Louvain algorithm. We show that this algorithm has a major defect that largely went unnoticed until now: the Louvain algorithm may yield arbitrarily badly connected communities. In the worst case, communities may even be disconnected, especially when running the algorithm iteratively. In our experimental analysis, we observe that up to 25% of the communities are badly connected and up to 16% are disconnected. To address this problem, we introduce the Leiden algorithm. We prove that the Leiden algorithm yields communities that are guaranteed to be connected. In addition, we prove that, when the Leiden algorithm is applied iteratively, it converges to a partition in which all subsets of all communities are locally optimally assigned. Furthermore, by relying on a fast local move approach, the Leiden algorithm runs faster than the Louvain algorithm. We demonstrate the performance of the Leiden algorithm for several benchmark and real-world networks. We find that the Leiden algorithm is faster than the Louvain algorithm and uncovers better partitions, in addition to providing explicit guarantees.

Complex Network Analysis TechniquesMobile Crowdsensing and CrowdsourcingAdvanced Graph Neural NetworksPartition (number theory)Benchmark (surveying)Efficient algorithmCommunity structureYield (engineering)
Citations
4,881
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References
Community detection algorithms: A comparative analysis
Physical Review E · 2009 · 2,189 citations
Benchmark graphs for testing community detection algorithms
Physical Review E · 2008 · 3,021 citations
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Physical Review E · 2006 · 2,077 citations
Finding community structure in very large networks
Physical Review E · 2004 · 7,389 citations
Performance of modularity maximization in practical contexts
Physical Review E · 2010 · 952 citations
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