title: Visual matrix clustering of social networks.
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.
authors.forename: Pak Chung
authors.initials: PC
authors.lastname: Wong
authors.forename: Patrick
authors.initials: P
authors.lastname: Mackey
authors.forename: Harlan
authors.initials: H
authors.lastname: Foote
authors.forename: Richard
authors.initials: R
authors.lastname: May