Community detection

Community detection algorithms are used to evaluate how groups of nodes are clustered or partitioned, as well as their tendency to strengthen or break apart. The Neo4j GDS library includes the following community detection algorithms, grouped by quality tier:

• Production-quality

  • Clique counting

  • Conductance metric

  • HDBSCAN

  • K-Core Decomposition

  • K-1 Coloring

  • K-Means Clustering

  • Label Propagation

  • Leiden

  • Local Clustering Coefficient

  • Louvain

  • Modularity metric

  • Modularity Optimization

  • Strongly Connected Components

  • Triangle Count

  • Weakly Connected Components

• Alpha

  • Approximate Maximum k-cut

  • Speaker-Listener Label Propagation