Leiden Repository (Leiden University)· 2019
From Louvain to Leiden: guaranteeing well-connected communities
- 4,329citations
- 2019year
Short summary
A new algorithm, Leiden, guarantees connected communities in network analysis, unlike the widely-used Louvain algorithm which can produce disconnected communities.
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Key points
- Louvain algorithm can yield disconnected communities (up to 16% observed).
- Leiden algorithm guarantees connected communities.
- Leiden algorithm converges to locally optimal partitions iteratively.
- Leiden algorithm is faster and produces better partitions than Louvain.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Leiden Repository (Leiden University), 2019 · DOI ↗
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Field: Statistical and Nonlinear Physics
Statistical and Nonlinear PhysicsPhysics and Astronomy