社交网络中一种基于模块化的社区检测算法

摘要

The existing community detection algorithms cannot act on the dynamic social networks where social activities and interactions are evolving rapidly. To solve this problem, this paper presents a quick community-detection algorithm, which can quickly and efficiently update network communities by using the network structures identified from the previous network knowledge, and then an adaptive modularity-based method is proposed for identifying and tracing community structure of dynamic online social networks. To illustrate the effectiveness of the algorithm, it extensively tests the proposed algorithm on real-world dynamic social networks. The experimental results show that social-aware routing strategies employing the proposed algorithm as community detection core outperforms the MIEN algorithm and the Blondel algorithm.%现有社区检测算法无法对社交活动和交互行为迅速发展的动态社交网络进行有效检测。为此，提出一种社区快速检测算法。使用现有网络知识确定的网络结构来更新网络社区，利用模块化技术自适应地检测和跟踪动态在线社交网络的社区结构。基于现实世界的动态社交网络对该算法进行测试，实验结果表明，使用该算法作为社区检测内核的社交感知路由策略，其性能要优于MIEN算法和Blondel算法。