InfoMagnets: Visualizing Connections in Networks

Making sense of information in large network datasets has become a challenge in many domains. A novel visu- alization method, the InfoMagnets diagram, which improves readability of network connections by aligning nodes and edges to a grid. It avoids edge crossing, displays symmetry of graph structure and promots continuity and regularity, which meets the requirements of the cognitive measurements of graph aesthetics. Inspired by the magnetic field model of magnets, interactions for the proposed new method are introduced, which brings natural and authentic user experience. This paper describes design and evaluation experiments related to the InfoMag- nets diagram. User behavior patterns are discovered using eye tracking methodology. And an application to visu- alize the connections in Wikipedia data is proposed. The development was motivated by a need for understand- ing relations between different academic fields but it is also useful in many other application domains such as social network analysis, ontology visualization and node-based visual scripting.