विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| सामाजिक नेटवर्क विश्लेषण× | निकटता केंद्रीयता (Closeness Centrality)× | |
|---|---|---|
| क्षेत्र | नेटवर्क विश्लेषण | नेटवर्क विश्लेषण |
| परिवार | Machine learning | Machine learning |
| उद्भव वर्ष≠ | 1934 (sociometry); 1994 (modern formalization) | 1950 (formalized 1979) |
| प्रवर्तक≠ | Moreno, J.L.; formalized by Wasserman & Faust | Bavelas, A.; formalized by Freeman, L. C. |
| प्रकार≠ | Structural/relational analysis framework | Node-level centrality index |
| मौलिक स्रोत≠ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 | Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239. DOI ↗ |
| उपनाम | SNA, network analysis, sociometric analysis, relational analysis | closeness, farness-based centrality, geodesic closeness, normalized closeness centrality |
| संबंधित≠ | 5 | 6 |
| सारांश≠ | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. | Closeness centrality measures how quickly a node can reach all others in a network by computing the inverse of its average shortest-path distance to every other node. First described by Bavelas (1950) and formally unified by Freeman (1979), it identifies nodes that can spread information or resources efficiently across the entire graph — not merely nodes with many direct contacts. |
| ScholarGateडेटासेट ↗ |
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