GalaxyExplorer: Influence-Driven Visual Exploration of Context-Specific Social Media Interactions

The ever-increasing size and complexity of social networks place a fundamental challenge to visual exploration and analysis tasks. In this paper, we present GalaxyExplorer, an influence-driven visual analysis system for exploring users of various influence and analyzing how they influence others in a social network. GalaxyExplorer reduces the size and complexity of a social network by dynamically retrieving theme-based graphs, and analyzing users’ influence and passivity regarding specific themes and dynamics in response to disaster events. In GalaxyExplorer, a galaxy-based visual metaphor is introduced to simplify the visual complexity of a large graph with a focus+context view. Various interactions are supported for visual exploration. We present experimental results on real-world datasets that show the effectiveness of GalaxyExplorer in theme-aware influence analysis.