ViStruclizer: A Structural Visualizer for Multi-dimensional Social Networks
Conference Proceeding Article
With the popularity of Web 2.0 sites, social networks today increasingly involve different kinds of relationships among different types of users in a single network. Such social networks are said to be multi-dimensional. Analyzing multi-dimensional networks is a challenging research task that requires intelligent visualization techniques. In this paper, we therefore propose a visual analytics tool called ViStruclizer to analyze structures embedded in a multi-dimensional social network. ViStruclizer incorporates structure analyzers that summarize social networks into both node clusters each representing a set of users, and edge clusters representing relationships between users in the node clusters. ViStruclizer supports user interactions to examine specific clusters of users and inter-cluster relationships, as well as to refine the learnt structural summary.
Data Mining and Knowledge Discovery, Artificial Intelligence (incl. Robotics), Information Storage and Retrieval
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Advances in Knowledge Discovery and Data Mining: 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II
City or Country
Gold Coast, Australia
DAI, Bingtian; Kwee, Agus Trisnajaya; and LIM, Ee Peng.
ViStruclizer: A Structural Visualizer for Multi-dimensional Social Networks. (2013). Advances in Knowledge Discovery and Data Mining: 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II. 7819, 49-60. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1893