विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| निर्देशित मध्यस्थता केंद्रीयता× | निर्देशित आइगेनवेक्टर केन्द्रीयता× | |
|---|---|---|
| क्षेत्र | नेटवर्क विश्लेषण | नेटवर्क विश्लेषण |
| परिवार | Machine learning | Machine learning |
| उद्भव वर्ष≠ | 1977 | 1972–1987 |
| प्रवर्तक≠ | Freeman, L. C. | Bonacich, P. |
| प्रकार≠ | Centrality measure (directed graph) | Centrality measure (eigenvector-based, directed) |
| मौलिक स्रोत≠ | Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗ | Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182. DOI ↗ |
| उपनाम | directed BC, digraph betweenness, asymmetric betweenness centrality, directed Freeman betweenness | directed EC, asymmetric eigenvector centrality, right eigenvector centrality, left eigenvector centrality |
| 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 eigenvector centrality extends the classic eigenvector centrality to directed graphs by scoring each node according to the centrality of the nodes that point to it (in-direction) or that it points to (out-direction). A node earns a high score not merely by having many connections but by being connected to other highly central nodes, capturing asymmetric influence in citation networks, social hierarchies, and information flows. |
| ScholarGateडेटासेट ↗ |
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