Identification of hybrid node and link communities in complex networks

Identification of hybrid node and link communities in complex networks

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organization...

Markov Dynamics based on Link-node-link Random Walk to Reveal Link Communities in Complex Networks

Discovery of communities in complex networks is a fundamental data analysis problem with many applications in various domains. Most of the existing approaches have focused on discovering communities of nodes, while recent studies have shown great advantage and utility of the knowledge of communities of links in networks. Aiming to address this new problem, we introduce a stochastic model based ...

Combined node and link partitions method for finding overlapping communities in complex networks

Community detection in complex networks is a fundamental data analysis task in various domains, and how to effectively find overlapping communities in real applications is still a challenge. In this work, we propose a new unified model and method for finding the best overlapping communities on the basis of the associated node and link partitions derived from the same framework. Specifically, we...

Discovering link communities in complex networks by exploiting link dynamics

Discovery of communities in complex networks is a fundamental data analysis problem with applications in various domains. Most of the existing approaches have focused on discovering communities of nodes, while recent studies have shown great advantages and utilities of the knowledge of communities of links in networks. From this new perspective, we propose a link dynamics based algorithm, calle...

Communities in Complex Networks: Identification at different levels