The stability of centrality measures when networks are sampled
The stability of centrality measures when networks are sampled
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DOI：
10.1016/s0378-8733(03)00012-1
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发表时间：
2003-10-01
期刊：
影响因子：
3.1
通讯作者：
Valente, TW
中科院分区：
文献类型：
--
作者：
Costenbader, E;Valente, TW
测量社交网络中心性的能力在社交网络分析中是一个特别有用的发展。对于试图决定哪种中心性测度对他们的研究目的最有意义和有效的研究人员来说，各种论文都探讨了中心性测度的概念基础。较少有文献记载的是在不同的研究情景或约束条件下的中心性措施的实证表现。本研究使用自助抽样程序，以确定如何影响11个不同的网络中心性措施的稳定性抽样。结果表明，一些措施是更稳定的比别人，稳定性也是一个功能的网络和学习属性。(C)2003 Elsevier B.V.保留所有权利。
The ability to measure centrality in social networks has been a particularly useful development in social network analysis. For researchers trying to decide which centrality measure is most meaningful and valid for their research purposes, various papers have explored the conceptual foundations of centrality measures. Less well documented is the empirical performance of centrality measures under different research scenarios or constraints. This study uses bootstrap sampling procedures to determine how sampling affects the stability of 11 different network centrality measures. Results indicate that some measures are more stable than others, and that stability is also a function of network and study properties. (C) 2003 Elsevier B.V. All rights reserved.