Title :
MultiStory: Visual analytics of dynamic multi-relational networks
Author :
Meidiana, Amyra ; Seok-Hee Hong
Author_Institution :
Univ. of Sydney, Sydney, NSW, Australia
Abstract :
Modern-day social networks are often dynamic and multi-relational, however there is currently little being studied on how to incorporate both aspects simultaneously to support visual analytic tasks for such complex social networks. We present a visual analytic framework for dynamic multi-relational networks and a prototype implementation, called the MultiStory system, which includes two new visualisation methods, AlterCluster and InterArc, designed for dynamic networks with multiple relations. The system is evaluated with two case studies using social networks from the MIT Reality Commons to demonstrate the effectiveness of the system to support a variety of visual analytical tasks on dynamic multi-relational networks.
Keywords :
complex networks; data analysis; data visualisation; graph theory; mathematics computing; network theory (graphs); AlterCluster; InterArc; MultiStory system; complex social network; dynamic multirelational network; visual analytics; Blogs; Communities; Data visualization; Marine vehicles; Social network services; Visual analytics; Graph/Network Data; Time Series Data; Visual Knowledge Discovery; Visualization in Social and Information Sciences;
Conference_Titel :
Visualization Symposium (PacificVis), 2015 IEEE Pacific
Conference_Location :
Hangzhou
DOI :
10.1109/PACIFICVIS.2015.7156359