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.

翻译：在网络分析中,已经开发了许多社区检测算法,但是,这些算法的实施没有解决对结果进行统计验证的问题。这里我们介绍Robin(ROBustness in Network),这是一个R包,用来评估以一种或多种方法发现的网络社区结构的稳健性,以表明其可靠性。该程序首先检测一组算法发现的社区结构是否具有统计意义,然后比较同一图上的两个选定的检测算法,以选择更适合网络的。我们展示了美国学院足球基准数据集的使用情况。