Louvain Community Detection

Overview

Louvain algorithm detects communities by optimizing modularity — the fraction of edges within communities minus expected fraction if edges were random. A greedy, hierarchical algorithm that runs in O(n log n) for sparse graphs. Produces a hierarchy of communities at multiple resolutions.

When to Use

Trigger conditions:

• Discovering natural groupings in social, organizational, or interaction networks
• Segmenting users/customers by behavioral similarity
• Analyzing modular structure of complex networks

When NOT to use:

• For overlapping communities (use DEMON or BigCLAM)
• When communities are pre-defined and you're classifying nodes (use label propagation)

Algorithm