方法证据记录
Weighted Eigenvector Centrality
Weighted eigenvector centrality extends the classic eigenvector centrality measure to graphs where edges carry numerical weights, scoring each node proportionally to the sum of its neighbors' scores multiplied by the connecting edge weights. Nodes score highly not just by having many connections but by being strongly linked to other influential nodes, making the measure sensitive to both tie strength and network position simultaneously.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Weighted Eigenvector Centrality (Spectral Prestige in Weighted Networks)
分类方法记录 · ml-model / network-analysis
- Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182. · DOI 10.1086/228631
- Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. · DOI 10.1016/j.socnet.2010.03.006
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