The investigation of community structures is one of the most important problems in the field of complex networks and has countless applications in different disciplines: biology, computer, social sciences, etc. Many community detection algorithms have been developed in various fields recently....

The investigation of community structure in networks is an important issue in many disciplines, which still remains a challenging task. First, complex networks often show a hierarchical structure with communities embedded within other communities. Moreover, communities in the network may overlap...

Based on the dynamics towards synchronization in hierarchical networks, we present an efficient method for extracting hierarchical organization in complex network. In the synchronization process, hierarchical structures corresponding to well defined communities of nodes emerge in different time...

Community detection is one of the most investigated problems in the field of complex networks. Although several methods were proposed, there is still no precise definition of communities. As a step toward a definition, I highlight two necessary properties of communities, separation and internal...

Decomposing a network into small modules or communities is beneficial for understanding the structure and dynamics of the network. One of the most prominent approaches is to repeatedly join communities together in pairs with the greatest increase in modularity so that a dendrogram that shows the...

Community detection is of considerable interest for analyzing the structure and function of complex networks. Recently, a type of multi-resolution methods in community detection was introduced, which can adjust the resolution of modularity by modifying the modularity function with tunable...

Community detection is one of the most important problems in complex networks. Many algorithms have been proposed in the last decade, and most of them focus on the non-overlapping community structures in the early days. Overlapping and hierarchical structures are another two important properties...

Complex networks are widely applied in every aspect of human society, and community detection is a research hotspot in complex networks. Many algorithms use modularity as the objective function, which can simplify the algorithm. In this paper, a community detection method based on modularity and...

Recent years have witnessed a growing recognition on the community detection in networks. Diverse techniques have been devoted to uncovering community structures in complex networks and amongst which are the density-based methods. Density-based avenues are very popular in data clustering field....

In recent studies of the complex network, most of the community detection methods only consider the network topological structure without background information. This leads to a relatively low accuracy. In this paper, a novel semi-supervised community detection algorithm is proposed based on the...