विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| निर्देशित मध्यस्थता केंद्रीयता× | निर्देशित निकटता केन्द्रीयता× | |
|---|---|---|
| क्षेत्र | नेटवर्क विश्लेषण | नेटवर्क विश्लेषण |
| परिवार | Machine learning | Machine learning |
| उद्भव वर्ष≠ | 1977 | 1979–1994 |
| प्रवर्तक≠ | Freeman, L. C. | Freeman, L. C.; Wasserman, S. & Faust, K. |
| प्रकार≠ | Centrality measure (directed graph) | Centrality measure |
| मौलिक स्रोत≠ | Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38269-4 |
| उपनाम | directed BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness | directed closeness, in-closeness centrality, out-closeness centrality, directional closeness |
| संबंधित | 5 | 5 |
| सारांश≠ | 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. | 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. |
| ScholarGateडेटासेट ↗ |
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