OLCPM: An Online Framework for Detecting Overlapping Communities in Dynamic Social Networks

TL;DR

OLCPM is an online algorithm that efficiently detects overlapping communities in dynamic social networks by locally updating community structures, combining clique percolation and label propagation techniques.

Contribution

It introduces OLCPM, a novel online method for detecting overlapping communities in temporal networks with improved efficiency over previous clique percolation approaches.

Findings

Effective detection of overlapping communities in dynamic networks.

Significant improvement in running time compared to previous methods.

Validated on both synthetic and real-world networks.

Abstract

Community structure is one of the most prominent features of complex networks. Community structure detection is of great importance to provide insights into the network structure and functionalities. Most proposals focus on static networks. However, finding communities in a dynamic network is even more challenging, especially when communities overlap with each other. In this article , we present an online algorithm, called OLCPM, based on clique percolation and label propagation methods. OLCPM can detect overlapping communities and works on temporal networks with a fine granularity. By locally updating the community structure, OLCPM delivers significant improvement in running time compared with previous clique percolation techniques. The experimental results on both synthetic and real-world networks illustrate the effectiveness of the method.