Visual Analytics of Social Networks: Mining and Visualizing Co-authorship Networks

被引:0
|
作者
Leung, Carson Kai-Sang [1 ]
Carmichael, Christopher L. [1 ]
Teh, Eu Wern [1 ]
机构
[1] Univ Manitoba, Winnipeg, MB, Canada
关键词
Human-computer interaction; data mining; frequent patterns; social network analysis and mining; social computing; social information; data visualization; information and knowledge visualization; visualizing social interaction; augmented cognition; FREQUENT; INTELLIGENCE; TREE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Co-authorship networks are examples of social networks, in which researchers are linked by their joint publications. Like many other instances of social networks, co-authorship networks contain rich sets of valuable data. In this paper, we propose a visual analytic tool, called SocialVis, to analyze and visualize these networks. In particular, SocialVis first applies frequent pattern mining to discover implicit, previously unknown and potential useful social information such as teams of multiple frequently collaborating researchers, their composition, and their collaboration frequency. SocialVis then uses a visual representation to present the mined social information so as to help users get a better understanding of the networks.
引用
收藏
页码:335 / 345
页数:11
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