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	Directed Closeness Centrality	有向介数中心性
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	1979–1994	1977
提唱者	Freeman, L. C.; Wasserman, S. & Faust, K.	Freeman, L. C.
種類	Centrality measure	Centrality measure (directed graph)
原典	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38269-4	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
別名	directed closeness, in-closeness centrality, out-closeness centrality, directional closeness	directed BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness
関連	5	5
概要	Directed closeness centrality extends the classical closeness measure to directed networks by separately quantifying how quickly a node can be reached by others (in-closeness) and how quickly it can reach all others (out-closeness). It is a foundational node-level metric in social network analysis and graph theory, used wherever link direction conveys meaningful asymmetry such as citation flows, information cascades, or authority hierarchies.	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.