Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Centralita směrované blízkosti× | Směrová centrality mezilehlosti× | |
|---|---|---|
| Obor | Analýza sítí | Analýza sítí |
| Rodina | Machine learning | Machine learning |
| Rok vzniku≠ | 1979–1994 | 1977 |
| Tvůrce≠ | Freeman, L. C.; Wasserman, S. & Faust, K. | Freeman, L. C. |
| Typ≠ | Centrality measure | Centrality measure (directed graph) |
| Původní zdroj≠ | 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. DOI ↗ |
| Další názvy | directed closeness, in-closeness centrality, out-closeness centrality, directional closeness | directed BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | 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. |
| ScholarGateDatová sada ↗ |
|
|