Title :
Visual Matrix Clustering of Social Networks
Author :
Pak Chung Wong ; Mackey, Patrick ; Foote, H. ; May, Ryan
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;
Journal_Title :
Computer Graphics and Applications, IEEE
DOI :
10.1109/MCG.2013.66