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加权社会网络分析×加权度中心性×
领域网络分析网络分析
方法族Machine learningMachine learning
起源年份2004–20102004
提出者Barrat, A.; Opsahl, T. et al.Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
类型Network analysis frameworkCentrality measure for weighted networks
开创性文献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 ↗
别名Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysisnode strength, strength centrality, weighted node degree, WDC
相关66
摘要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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  3. PUBLISHED

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ScholarGate方法对比: Weighted Social Network Analysis · Weighted Degree Centrality. 于 2026-06-19 检索自 https://scholargate.app/zh/compare