Visual matrix clustering of social networks
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Updated: Apr 30, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
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.
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