2014 International Conference on Big Data and Smart Computing (BIGCOMP) (2014)
Jan. 15, 2014 to Jan. 17, 2014
Seok-Hee Hong , School of IT, University of Sydney, Australia
Weidong Huang , School of Engineering and ICT, University of Tasmania, Launceston, Australia
Kazuo Misue , Faculty of Engineering, Information and Systems, University of Tsukuba, Japan
Wu Quan , Business School, University of Sydney, Australia
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.
Social Networks, Visual Analytics, Web of Science, Graph Drawing
Seok-Hee Hong, Weidong Huang, K. Misue and Wu Quan, "A framework for visual analytics of massive complex networks," 2014 International Conference on Big Data and Smart Computing (BIGCOMP), Bangkok, Thailand, 2014, pp. 22-28.