A framework for visual analytics of massive complex networks

In this paper, we present a framework for visual analytics of massive complex networks. Our framework is based on the tight integration of network analysis methods with visualization methods to address the scalability and complexity. We present case studies using various networks derived from the WoS (Web of Science). More specifically, we integrated co-citation analysis of Social Network community with 2.5D visualization methods to provide insight and overview on temporal dynamics. Furthermore, we derived collaboration networks and citation networks of Graph Drawing community and visualized using Anchored map techniques to understand collaboration patterns between important researchers in the community.