加权社交网络节点中心性计算模型

A Node Centrality Evaluation Model for Weighted Social Networks

摘要: 将无权网络中度量节点中心性的方法——主分量中心性(principal component centrality)应用于加权社交网络，提出基于链接强度矩阵的加权中心性度量法. 实验结果显示，加权主分量中心性在传播效率、鲁棒性和容错性等方面优于加权特征向量中心性(eigenvector centrality)，因此加权主分量中心性在加权社交网络中是可行有效的.

Abstract: In this paper, we apply Principal Component Centrality (PCC), a centrality measure for unweighted networks, to weighted social networks, and propose a weighted centrality measure based on tie strength matrix (TSM). Experiment results show that weighted PCC outperforms weighted EVC (EigenVector Centrality) in spreading effectiveness, robustness and tolerance, hence is feasible and effective in weighted social networks.