  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.
