Social Viewpoint Finder (SVF) is a visual analytics tool for social networks and complex networks. SVF lays out the input network data on a HIGH-dimensional (500-3,000 dimensional) Euclidean space, offers a simple, but unique dragging-based UI to trigger computation-intensive, high-dimensional rota- tion of the presented network, and let the user investigate the clustering structure of the network. This demonstration presents the effectiveness of SVF as well as the employed implementation techniques that enabled the fluid, complex user interaction. To achieve fluidness, SVF heavily relies on modern OpenGL technologies. It achieves massively parallel computing through the use of the compute shader, and graphic pipelines. A large volume of the network data and its layout information is stored in a shader storage buffer. A fragment shader-based, efficient object identification method is devised.
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