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Egocentric Network Exploration for Immersive Analytics

Authors :
Sorger, Johannes
Arleo, Alessio
Kán, Peter
Knecht, Wolfgang
Waldner, Manuela
Publication Year :
2021

Abstract

To exploit the potential of immersive network analytics for engaging and effective exploration, we promote the metaphor of "egocentrism", where data depiction and interaction are adapted to the perspective of the user within a 3D network. Egocentrism has the potential to overcome some of the inherent downsides of virtual environments, e.g., visual clutter and cyber-sickness. To investigate the effect of this metaphor on immersive network exploration, we designed and evaluated interfaces of varying degrees of egocentrism. In a user study, we evaluated the effect of these interfaces on visual search tasks, efficiency of network traversal, spatial orientation, as well as cyber-sickness. Results show that a simple egocentric interface considerably improves visual search efficiency and navigation performance, yet does not decrease spatial orientation or increase cyber-sickness. An occlusion-free Ego-Bubble view of the neighborhood only marginally improves the user's performance. We tie our findings together in an open online tool for egocentric network exploration, providing actionable insights on the benefits of the egocentric network exploration metaphor.<br />Comment: Pacific Graphics 2021, Volume 40 (2021), Number 7

Subjects

Subjects :
Computer Science - Graphics

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2109.09547
Document Type :
Working Paper