Machine learningNetwork science
有向介数中心性
有向介数中心性（Directed Betweenness Centrality）是对弗里曼（Freeman）经典介数中心性度量在有向图上的扩展，它量化了一个节点在所有其他节点对之间的最短有向路径上出现的频率。它能够识别不对称流动（如信息级联、引文网络和组织层级结构）中的关键节点、中介者和瓶颈。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI: 10.2307/3033543 ↗
- Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2), 163–177. DOI: 10.1080/0022250X.2001.9990249 ↗
如何引用本页
ScholarGate. (2026, June 3). Directed Betweenness Centrality (Freeman's Betweenness on Directed Graphs). ScholarGate. https://scholargate.app/zh/network-analysis/directed-betweenness-centrality
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 中间性中心度网络分析↔ compare
- 有向紧密度中心性网络分析↔ compare
- 有向特征向量中心性网络分析↔ compare
- 定向PageRank网络分析↔ compare
- 定向社交网络分析网络分析↔ compare