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Visual Matrix Clustering of Social Networks
July-Aug. 2013 (vol. 33 no. 4)
pp. 88-96
Pak Chung Wong, Pacific Northwest National Laboratory
Patrick Mackey, Pacific Northwest National Laboratory
Harlan Foote, Pacific Northwest National Laboratory
Richard May, Pacific Northwest National Laboratory
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.
Index Terms:
Social network services,Data visualization,Visualization,Image color analysis,Visual analytics,Geospatial analysis,Sociology,computer graphics,adjacency matrix,node-link graph,social networks,visualization,visual analytics
Pak Chung Wong, Patrick Mackey, Harlan Foote, Richard May, "Visual Matrix Clustering of Social Networks," IEEE Computer Graphics and Applications, vol. 33, no. 4, pp. 88-96, July-Aug. 2013, doi:10.1109/MCG.2013.66
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