A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental evaluation of the reviewed methods to answer three main questions: to what extent the evaluated methods are able to detect ground-truth communities, to what extent different methods produce similar community structures, and to what extent the evaluated methods are scalable. One goal of this survey is to help scholars and practitioners to choose the right methods for the data and the task at hand, while also emphasizing when such choice is problematic.

中文翻译：

---

多路网络中的社区检测

多路复用网络对相同类型实体之间的不同交互模式进行建模。在本文中，我们提供了多路网络中社区检测算法的分类。我们根据各种属性来描述不同的算法，并讨论每种方法检测到的社区类型。然后，我们对所审查的方法进行广泛的实验评估，以回答三个主要问题：评估的方法在多大程度上能够检测到真实社区，不同的方法在多大程度上产生相似的社区结构，以及评估的方法在多大程度上是可扩展的。这项调查的一个目标是帮助学者和从业者为数据和手头的任务选择正确的方法，同时也强调这种选择何时有问题。