Chapter 10. Finding Beautiful Insights in the Chaos of Social Network Visualizations

Adam Perer


My purpose throughout is to interpret the material by juxtaposing and assembling the notations into a unified, coherent whole.

Mark Lombardi

MARK LOMBARDI WAS PERHAPS THE PERFECT NETWORK LAYOUT ALGORITHM. As an artist intent on communicating complex networks of financial and political scandals, he diligently drew networks where nodes never overlap, edges rarely cross, and the connections are smooth and curvy (Figure 10-1). This amount of grace and sensitivity is rarely present in the visualizations of social networks created by computational means. While advanced computational layout algorithms may be grounded in physical models of springs and forces, they rarely highlight patterns and trends like Lombardi's drawings do. This chapter details my attempts to empower users to dig deeper into these chaotic social network visualizations with interactive techniques that integrate visualization and statistics.

Visualizing Social Networks

The increasing amount of digital information in modern society has ushered in a golden age for data analysis. Ample data encourages users to conduct more frequent exploratory data analyses to explain scientific, social, cultural, and economic phenomena. However, while access to data is important, it is ultimately insufficient unless we also have the ability to understand patterns, identify outliers, and discover gaps. Modern databases are simply too large ...

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