Machine learningNetwork science

Directed Modularity Analysis

Directed modularity analysis extends the classic Newman-Girvan modularity framework to directed graphs, where edges carry a source and a destination. Formalized by Leicht and Newman in 2008, it partitions nodes into communities by maximizing a modularity score that accounts for each node's separate in-degree and out-degree in the null model, making it the standard approach for community detection in citation networks, information flows, and other asymmetric relational data.

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Sources

  1. Leicht, E. A., & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. DOI: 10.1103/PhysRevLett.100.118703
  2. Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113. DOI: 10.1103/PhysRevE.69.026113

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Referenced by

ScholarGateDirected Modularity Analysis (Directed Modularity Analysis (Leicht-Newman Directed Community Detection)). Retrieved 2026-06-04 from https://scholargate.app/tr/network-analysis/directed-modularity-analysis