Community detection is one of the most important issues in modern network science. Although numerous community detection algorithms have been proposed during the past decades, how to assess the statistical significance of one single community analytically and exactly still remains an open problem. In this paper, we present an analytical solution to calculate the exact p-value of a single community with the Erdös–Rényi model. Meanwhile, we propose a local search method for finding statistically significant communities based on the p-value minimization. Experimental results on both real networks and simulated networks demonstrate that our method is able to effectively detect true communities from different types of networks.

中文翻译：

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计算精确的P值以进行社区检测

社区检测是现代网络科学中最重要的问题之一。尽管在过去的几十年中已经提出了许多社区检测算法，但是如何通过分析准确地评估一个社区的统计意义仍然是一个悬而未决的问题。在本文中，我们提出了一种解析解决方案，可以使用Erdös–Rényi模型计算单个社区的确切p值。同时，我们提出了一种基于p值最小化的具有统计学意义的社区搜索方法。在真实网络和模拟网络上的实验结果表明，我们的方法能够有效地检测来自不同类型网络的真实社区。