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| 가중치 사회 연결망 분석 (Weighted Social Network Analysis)× | 가중 차수 중심성× | |
|---|---|---|
| 분야 | 네트워크 분석 | 네트워크 분석 |
| 계열 | Machine learning | Machine learning |
| 기원 연도≠ | 2004–2010 | 2004 |
| 창시자≠ | Barrat, A.; Opsahl, T. et al. | Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A. |
| 유형≠ | Network analysis framework | Centrality measure for weighted networks |
| 원전 | Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗ | Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗ |
| 별칭 | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis | node strength, strength centrality, weighted node degree, WDC |
| 관련 | 6 | 6 |
| 요약≠ | Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships. | Weighted degree centrality — also called node strength — extends the classic degree centrality measure to networks whose edges carry numeric weights. Instead of simply counting a node's connections, it sums the weights of all edges incident to that node, capturing both the volume and the intensity of a node's ties in a single, interpretable score. |
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