What Do Centrality Measures Measure in Psychological Networks?
What Do Centrality Measures Measure in Psychological Networks?
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DOI：
10.1037/abn0000446
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发表时间：
2019-11-01
影响因子：
4.6
通讯作者：
Snippe, Evelien
中科院分区：
文献类型：
--
作者：
Bringmann, Laura F.;Elmer, Timon;Snippe, Evelien
中心性指数是分析心理网络结构方面的流行工具。由于中心性指数最初是在社会网络的背景下开发的，目前还不清楚这些指数在多大程度上适用于心理网络背景。在这篇文章中，我们使用心理网络中最流行的中心性指数来批判性地检查几个问题：程度、中间性和接近中心性。我们发现，社会网络文献中讨论的中心性指数问题也适用于心理网络。中心性指数的基本假设，如流量和最短路径的存在。可能与心理变量如何相互关联的一般理论不符。此外，心理网络中关于节点区分性和节点互换性的假设可能不成立。我们得出这样的结论。对于心理网络来说，中间度和贴近度中心度似乎特别不适合作为节点重要性的衡量标准。因此，我们建议采取三种方法：(A)使用针对心理网络背景量身定做的中心性衡量标准。(B)重新考虑心理网络基础统计模型中使用的现有重要性衡量标准，以及(C)完全摒弃节点中心性的概念。最重要的。我们认为，当一个人声明一个节点是中心时，你必须明确自己的意思，以及选择的中心性衡量标准需要什么假设，以确保正在研究的过程与使用的中心性衡量标准之间存在匹配。
Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this article we critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality. We show that problems with centrality indices discussed in the social network literature also apply to the psychological networks. Assumptions underlying centrality indices, such as presence of a flow and shortest paths. may not correspond with a general theory of how psychological variables relate to one another. Furthermore, the assumptions of node distinctiveness and node exchangeability may not hold in psychological networks. We conclude that. for psychological networks, betweenness and closeness centrality seem especially unsuitable as measures of node importance. We therefore suggest three ways forward: (a) using centrality measures that are tailored to the psychological network context. (b) reconsidering existing measures of importance used in statistical models underlying psychological networks, and (c) discarding the concept of node centrality entirely. Foremost. we argue that one has to make explicit what one means when one states that a node is central, and what assumptions the centrality measure of choice entails, to make sure that there is a match between the process under study and the centrality measure that is used.