网络中的鲁棒性(robin):一个用于社区比较和验证的R包

R J. Pub Date : 2021-02-05 DOI:10.32614/rj-2021-040
V. Policastro, D. Righelli, A. Carissimo, L. Cutillo, I. Feis
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引用次数: 3

摘要

在网络分析中,已经开发了许多社区检测算法,然而,它们的实现没有解决结果的统计验证问题。在这里,我们提出robin(鲁棒性网络),这是一个R包,用于评估通过一种或多种方法发现的网络社区结构的鲁棒性,以给出其可靠性的指示。该过程首先检测由一组算法发现的社区结构是否具有统计显著性,然后在同一图上比较选定的两种检测算法,以选择更适合感兴趣网络的算法。我们在美国大学橄榄球基准数据集上演示了我们的包的使用。
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ROBustness In Network (robin): an R Package for Comparison and Validation of Communities
In network analysis, many community detection algorithms have been developed, however, their implementation leaves unaddressed the question of the statistical validation of the results. Here we present robin(ROBustness In Network), an R package to assess the robustness of the community structure of a network found by one or more methods to give indications about their reliability. The procedure initially detects if the community structure found by a set of algorithms is statistically significant and then compares two selected detection algorithms on the same graph to choose the one that better fits the network of interest. We demonstrate the use of our package on the American College Football benchmark dataset.
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