Method evidence record
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.
Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.
Source record
Recorded
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Directed Closeness Centrality (In-closeness and Out-closeness on Directed Graphs)
Taxonomic method recordml-modelnetwork-analysis
Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. · ISBN 978-0-521-38269-4
Open full method2 recorded citations, copied from the method source record.
Curated claims
Assessed
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
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Related methods
Suggested5
Generated from the method graph and shown as machine-suggested relations. No evidence claim is inferred.
- Taxonomic bucketCloseness Centrality
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketDirected Betweenness Centrality
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketDirected Eigenvector Centrality
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketDirected PageRank
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketDirected Social Network Analysis
machine-suggestedRelational suggestion, not evidence.