Description
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. Leiden algorithm overcomes these problems.
Pointers
Work your way up from Louvain as it is described in the Appendix of the paper to Leiden.
Description 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. Leiden algorithm overcomes these problems.
Pointers Work your way up from Louvain as it is described in the Appendix of the paper to Leiden.
References https://www.nature.com/articles/s41598-019-41695-z https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-019-41695-z/MediaObjects/41598_2019_41695_MOESM1_ESM.pdf