Issue No.04 - July-Aug. (2013 vol.33)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2013.66
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.
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, P. Mackey, H. Foote, R. 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