有向网络中的社团结构
Community structure in directed networks
摘要：
我们考虑在有向网络中寻找社区或模块的问题。在以前的文献中，这个问题的最常见的方法是简单地忽略边缘方向和应用开发的方法在无向网络中的社区发现，但这种方法丢弃潜在的有用信息中包含的边缘方向。在这里，我们展示了如何被广泛使用的效益函数称为模块化，可以推广到一个原则性的方式，将包含在边缘方向的信息。这反过来又允许我们通过最大化网络可能划分的模块性来找到社区，我们使用基于相应模块性矩阵的特征向量的算法来实现这一点。这种方法被证明比以前的方法在各种测试网络，真实的和计算机生成的结果。
英文摘要：
We consider the problem of finding communities or modules in directed networks. The most common approach to this problem in the previous literature has been simply to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used benefit function known as modularity can be generalized in a principled fashion to incorporate the information contained in edge directions. This in turn allows us to find communities by maximizing the modularity over possible divisions of a network, which we do using an algorithm based on the eigenvectors of the corresponding modularity matrix. This method is shown to give demonstrably better results than previous methods on a variety of test networks, both real and computer-generated.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
