Community detection is one of the most popular researches in a variety of complex systems, ranging from biology to sociology. In recent years, there’s an increasing focus on the rapid development of more complicated networks, namely multilayer networks. Communities in a single-layer network are groups of nodes that are more strongly connected among themselves than the others, while in multilayer networks, a group of well-connected nodes are shared in multiple layers. Most traditional algorithms can rarely perform well on a multilayer network without modifications. Thus, in this paper, we offer overall comparisons of existing works and analyze several representative algorithms, providing a comprehensive understanding of community detection methods in multilayer networks. The comparison results indicate that the promoting of algorithm efficiency and the extending for general multilayer networks are also expected in the forthcoming studies.

社区检测是从生物学到社会学的各种复杂系统中最受欢迎的研究之一。近年来，人们越来越关注快速发展的更为复杂的网络，即多层网络。单层网络中的社区是相互之间比其他节点之间连接更牢固的节点组，而在多层网络中，一组连接良好的节点在多层中共享。如果不进行修改，大多数传统算法很少会在多层网络上表现良好。因此，在本文中，我们提供了对现有工作的整体比较，并分析了几种代表性算法，从而全面了解了多层网络中的社区检测方法。