The issue of network community detection has been extensively studied across many fields. Most community detection methods assume that nodes belong to only one community. However, in many cases, nodes can belong to multiple communities simultaneously.This paper presents two overlapping network community detection algorithms that build on the two-step approach, using the extended modularity and cosine function. The applicability of our algorithms extends to both undirected and directed graph structures. To demonstrate the feasibility and effectiveness of these algorithms, we conducted experiments using real data.

翻译：网络社区检测问题已在多个领域得到广泛研究。大多数社区检测方法假设节点仅属于一个社区，然而在许多情况下，节点可同时属于多个社区。本文提出两种基于两步法、利用扩展模块度与余弦函数的重叠网络社区检测算法，其适用性涵盖无向图与有向图结构。为验证算法的可行性与有效性，我们采用真实数据进行了实验。