Multiscale Visualization and Exploration of Large Bipartite Graphs

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dc.contributor.authorPezzotti, Nicolaen_US
dc.contributor.authorFekete, Jean-Danielen_US
dc.contributor.authorHöllt, Thomasen_US
dc.contributor.authorLelieveldt, Boudewijn P. F.en_US
dc.contributor.authorEisemann, Elmaren_US
dc.contributor.authorVilanova, Annaen_US
dc.contributor.editorJeffrey Heer and Heike Leitte and Timo Ropinskien_US
dc.date.accessioned2018-06-02T18:09:38Z
dc.date.available2018-06-02T18:09:38Z
dc.date.issued2018
dc.description.abstractA bipartite graph is a powerful abstraction for modeling relationships between two collections. Visualizations of bipartite graphs allow users to understand the mutual relationships between the elements in the two collections, e.g., by identifying clusters of similarly connected elements. However, commonly-used visual representations do not scale for the analysis of large bipartite graphs containing tens of millions of vertices, often resorting to an a-priori clustering of the sets. To address this issue, we present the Who's-Active-On-What-Visualization (WAOW-Vis) that allows for multiscale exploration of a bipartite socialnetwork without imposing an a-priori clustering. To this end, we propose to treat a bipartite graph as a high-dimensional space and we create the WAOW-Vis adapting the multiscale dimensionality-reduction technique HSNE. The application of HSNE for bipartite graph requires several modifications that form the contributions of this work. Given the nature of the problem, a set-based similarity is proposed. For efficient and scalable computations, we use compressed bitmaps to represent sets and we present a novel space partitioning tree to efficiently compute similarities; the Sets Intersection Tree. Finally, we validate WAOWVis on several datasets connecting Twitter-users and -streams in different domains: news, computer science and politics. We show how WAOW-Vis is particularly effective in identifying hierarchies of communities among social-media users.en_US
dc.description.number3
dc.description.sectionheadersTrees and Graphs
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13441
dc.identifier.issn1467-8659
dc.identifier.pages549-560
dc.identifier.urihttps://doi.org/10.1111/cgf.13441
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13441
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]
dc.subjectPicture/Image Generation
dc.subjectLine and curve generation
dc.titleMultiscale Visualization and Exploration of Large Bipartite Graphsen_US
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