Сравнение методов

	Взвешенный анализ социальных сетей	Взвешенная степень центральности
Область	Сетевой анализ	Сетевой анализ
Семейство	Machine learning	Machine learning
Год появления	2004–2010	2004
Автор метода	Barrat, A.; Opsahl, T. et al.	Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
Тип	Network analysis framework	Centrality measure for weighted networks
Основополагающий источник	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.	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.
Другие названия	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis	node strength, strength centrality, weighted node degree, WDC
Связанные	6	6
Сводка	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.