Louvain method: Finding communities in large networks

Using the Louvain version available on this web page is not recommended.

The current maintained version is available on sourceforge: sourceforge.net/projects/louvain/

In the last few years, there have been many attempts to uncover communities in large networks. By large, we mean systems composed of millions of nodes, which cannot be visualized nor analyzed at the level of single nodes and therefore require a coarse-grained description.

Our method, that we call Louvain Method (because, even though the co-authors now hold positions in Paris, London and Louvain, the method was devised when they all were in Louvain), outperforms other methods in terms of computation time, which allows us to analyze networks of unprecedented size (e.g. the analysis of a typical network of 2 million nodes only takes 2 minutes). The Louvain method has also been to shown to be very accurate by focusing on ad-hoc networks with known community structure. Moreover, due to its hierarchical structure, which is reminiscent of renormalization methods, it allows to look at communities at different resolutions.

The method consists of two phases. First, it looks for "small" communities by optimizing modularity in a local way. Second, it aggregates nodes of the same community and builds a new network whose nodes are the communities. These steps are repeated iteratively until a maximum of modularity is attained.