BACKGROUND Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has been so far devoted to the investigation of communities in real networks. METHODOLOGY/PRINCIPAL FINDINGS We present a systematic empirical analysi...

Based on a signaling process of complex networks, a method for identification of community structure is proposed. For a network with n nodes, every node is assumed to be a system which can send, receive, and record signals. Each node is taken as the initial signal source to excite the whole network one time. Then the source node is associated with an n -dimensional vector which records the effe...

Many networks are characterized by the presence of communities, densely intra-connected groups with sparser inter-connections between groups. We propose a community overlay network representation to capture large-scale properties of communities. A community overlay Go can be constructed upon a network G, called the underlying network, by (a) aggregating each community in G as a node in the over...

We present a new layout algorithm for complex networks that combines a multi-scale approach for community detection with a standard forcedirected design. Since community detection is computationally cheap, we can exploit the multi-scale approach to generate network configurations with close-to-minimal energy very fast. As a further asset, we can use the knowledge of the community structure to f...