We propose a new method to select the most appropriate network centrality measure based on the user's opinion on how such a measure should work on a set of simple graphs. The method consists in: (1) forming a set $\cal F$ of candidate measures; (2) generating a sequence of sufficiently simple graphs that distinguish all measures in $\cal F$ on some pairs of nodes; (3) compiling a survey with questions on comparing the centrality of test nodes; (4) completing this survey, which provides a centrality measure consistent with all user responses. The developed algorithms make it possible to implement this approach for any finite set $\cal F$ of measures. This paper presents its realization for a set of 40 centrality measures. The proposed method called culling can be used for rapid analysis or combined with a normative approach by compiling a survey on the subset of measures that satisfy certain normative conditions (axioms). In the present study, the latter was done for the subsets determined by the Self-consistency or Bridge axioms.

中文翻译：

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如何选择最合适的中心性度量？

我们提出了一种新方法，可以根据用户对此类度量应如何在一组简单图形上工作的意见来选择最合适的网络中心性度量。该方法包括： (1) 形成一组候选测量值；(2) 生成一系列足够简单的图来区分 $\cal F$ 中某些节点对上的所有度量；(3) 编制一份调查问卷，其中包含比较测试节点中心性的问题；(4) 完成这项调查，它提供了与所有用户响应一致的中心性度量。开发的算法可以为任何有限的度量集合 $\cal F$ 实现这种方法。本文介绍了它对一组 40 个中心性度量的实现。所提出的称为剔除的方法可用于快速分析，或通过对满足某些规范条件（公理）的措施子集进行调查，与规范方法相结合。在本研究中，后者是针对自洽公理或桥接公理确定的子集进行的。