Bicentric diagrams: Design and applications of a graph-based relational set visualization technique.

In an era where data on social, economic, and physical networks are proliferating at a rapid pace, the ability to understand the underlying complex structural connections, discover prominent entities, and identify clusters is becoming increasingly important. It is also well-established that interactive visualizations can amplify human cognition and augment decision making. Motivated by a practical need articulated by corporate decision makers and limitations of existing visual representations, this research presents our journey in designing and implementing bicentric diagrams, a novel graph-based set visualization technique. A bicentric diagram enables simultaneous identification of sets, set relationships, and set member reach in integrated egonetworks of two focal entities. Our technique builds on the well-established sociological theory of tie strength to visually group and position nodes. We illustrate the broad applicability of bicentric diagrams with examples from four diverse sample domains: university collaboration, technology co-occurrence, health app purchases, and interfirm alliance networks. We assess the value of our technique using an expert-based evaluation approach. The paper concludes with implications and a discussion of opportunities for implementation in real-world decision support settings.