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Ugunduzi wa Jumuiya Zinazoongozwa×Upeo wa Kati wa Uelekezaji×
NyanjaUchanganuzi wa MitandaoUchanganuzi wa Mitandao
FamiliaMachine learningMachine learning
Mwaka wa asili20081977
MwanzilishiLeicht, E. A. & Newman, M. E. J.; Rosvall, M. & Bergstrom, C. T.Freeman, L. C.
AinaGraph partitioning / modularity optimizationCentrality measure (directed graph)
Chanzo asiliaLeicht, E. A. & Newman, M. E. J. (2008). Community structure in directed networks. Physical Review Letters, 100(11), 118703. DOI ↗Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗
Majina mbadaladirected graph clustering, community detection in digraphs, directed modularity optimization, directed network partitioningdirected BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness
Zinazohusiana65
MuhtasariDirected community detection identifies densely interconnected groups of nodes in a directed network, accounting for the asymmetry of edges (e.g., A follows B does not imply B follows A). Adapting modularity or flow-based criteria to directed graphs reveals clusters that undirected methods systematically miss, making it essential for citation networks, follower graphs, and biological regulatory pathways.Directed Betweenness Centrality extends Freeman's classic betweenness measure to directed graphs, quantifying how often a node lies on the shortest directed paths between all other pairs of nodes. It identifies gatekeepers, brokers, and bottlenecks in asymmetric flows such as information cascades, citation networks, and organizational hierarchies.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Directed Community Detection · Directed Betweenness Centrality. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare