DocumentCode
46824
Title
Visual Matrix Clustering of Social Networks
Author
Pak Chung Wong ; Mackey, Patrick ; Foote, H. ; May, Ryan
Volume
33
Issue
4
fYear
2013
fDate
July-Aug. 2013
Firstpage
88
Lastpage
96
Abstract
The prevailing choices to graphically represent a social network are a node-link graph and an adjacency matrix. Both techniques have unique strengths and weaknesses for different domain applications. This article focuses on how to change adjacency matrices from merely showing pairwise associations among network actors (or graph nodes) to depicting clusters of a social network. Node-link graphs supplement the discussion.
Keywords
data visualisation; graph theory; matrix algebra; pattern clustering; social networking (online); adjacency matrix; node-link graph; pairwise association; social network representation; visual matrix clustering; Data visualization; Geospatial analysis; Image color analysis; Social network services; Sociology; Visual analytics; Visualization; adjacency matrix; computer graphics; node-link graph; social networks; visual analytics; visualization;
fLanguage
English
Journal_Title
Computer Graphics and Applications, IEEE
Publisher
ieee
ISSN
0272-1716
Type
jour
DOI
10.1109/MCG.2013.66
Filename
6562725
Link To Document