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Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Ważone centralności pośrednictwa× | Analiza sieci społecznych× | |
|---|---|---|
| Dziedzina | Analiza sieci | Analiza sieci |
| Rodzina | Machine learning | Machine learning |
| Rok powstania≠ | 2010 | 1934 (sociometry); 1994 (modern formalization) |
| Twórca≠ | Opsahl, T.; Agneessens, F.; Skvoretz, J. (extending Freeman 1977 and Brandes 2001) | Moreno, J.L.; formalized by Wasserman & Faust |
| Typ≠ | Centrality measure (path-based) | Structural/relational analysis framework |
| Źródło pierwotne≠ | Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Inne nazwy | WBC, weighted shortest-path betweenness, edge-weighted betweenness, geodesic betweenness (weighted) | SNA, network analysis, sociometric analysis, relational analysis |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | Weighted Betweenness Centrality extends Freeman's betweenness measure to edge-weighted graphs by routing shortest paths through a tunable transformation of edge weights. Nodes that sit on many high-value shortest paths receive high scores, identifying brokers and bridges in social, biological, and information networks where tie strength matters. | 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. |
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