Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Κεντρικότητα Εγγύτητας Κατευθυνόμενη× | Κατευθυνόμενη Κεντρικότητα Ενδιαμεσότητας× | |
|---|---|---|
| Πεδίο | Ανάλυση Δικτύων | Ανάλυση Δικτύων |
| Οικογένεια | Machine learning | Machine learning |
| Έτος προέλευσης≠ | 1979–1994 | 1977 |
| Δημιουργός≠ | Freeman, L. C.; Wasserman, S. & Faust, K. | Freeman, L. C. |
| Τύπος≠ | Centrality measure | Centrality measure (directed graph) |
| Θεμελιώδης πηγή≠ | 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 ↗ |
| Εναλλακτικές ονομασίες | directed closeness, in-closeness centrality, out-closeness centrality, directional closeness | directed BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness |
| Συναφείς | 5 | 5 |
| Σύνοψη≠ | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
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