Dossier de preuve de méthode

Directed Closeness Centrality

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.

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Directed Closeness Centrality (In-closeness and Out-closeness on Directed Graphs)

Dossier de méthode taxonomique · ml-model / network-analysis

Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. · ISBN 978-0-521-38269-4
Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239. · DOI 10.1016/0378-8733(78)90021-7

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Méthodes apparentées

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Taxonomic bucketCloseness Centralitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDirected Betweenness Centralitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDirected Eigenvector Centralitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDirected PageRankmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDirected Social Network Analysismachine-suggested · Relational suggestion, not evidence.