Assessing the consistency of community structure in complex networks.
Assessing the consistency of community structure in complex networks.
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DOI：
10.1103/physreve.84.016111
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发表时间：
2011-07
期刊：
影响因子：
--
通讯作者：
Laurienti P
中科院分区：
文献类型：
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作者：
Steen M;Hayasaka S;Joyce K;Laurienti P
近年来，社团结构已成为复杂网络分析的重要组成部分。随着收集到更多的数据，研究人员已经开始调查多个网络中不断变化的社区结构。有几种方法可以分析不断变化的社区，但大多数方法仅限于单个网络随时间的演变。此外，现有的大多数方法更关注社区级别的变化，而不是单个节点级别的变化。在本文中，我们引入了尺度包容性，这是一种量化网络中社区结构变化的方法。扩展的包含性独立评估网络中每个节点分类的一致性。此外，该方法既可以横向应用，也可以纵向应用。在这篇文章中，我们计算了一组模拟的美国城市网络和一组由美国大学橄榄球顶级联赛的球队组成的真实网络的尺度包容性。我们发现，扩展的包含性对两组网络中的单个节点的一致性产生了合理的结果。我们认为，扩展的包容性可以提供一种有用的方法来量化网络社区结构的变化。
In recent years, community structure has emerged as a key component of complex network analysis. As more data has been collected, researchers have begun investigating changing community structure across multiple networks. Several methods exist to analyze changing communities, but most of these are limited to evolution of a single network over time. In addition, most of the existing methods are more concerned with change at the community level than at the level of the individual node. In this paper, we introduce scaled inclusivity, which is a method to quantify the change in community structure across networks. Scaled inclusivity evaluates the consistency of the classification of every node in a network independently. In addition, the method can be applied cross-sectionally as well as longitudinally. In this paper, we calculate the scaled inclusivity for a set of simulated networks of United States cities and a set of real networks consisting of teams that play in the top division of American college football. We found that scaled inclusivity yields reasonable results for the consistency of individual nodes in both sets of networks. We propose that scaled inclusivity may provide a useful way to quantify the change in a network’s community structure.