Machine learningNetwork science
Betweenness Centrality
Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.
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Sources
- Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI: 10.2307/3033543 ↗
- Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177. DOI: 10.1080/0022250X.2001.9990249 ↗
Related methods
Referenced by
Bayesian Betweenness CentralityCloseness CentralityDegree CentralityDirected Betweenness CentralityDirected Knowledge Graph AnalysisDirected Modularity AnalysisDirected PageRankDirected Social Network AnalysisDynamic Closeness CentralityDynamic PageRankEigenvector CentralityModularity AnalysisMultilayer Betweenness CentralityMultiplex Network AnalysisNetwork Diffusion AnalysisSocial Network AnalysisTemporal Betweenness CentralityTemporal Closeness CentralityTwo-mode Network AnalysisWeighted Betweenness CentralityWeighted Degree CentralityWeighted Ego Network AnalysisWeighted Modularity AnalysisWeighted PageRankWeighted Social Network Analysis