TimeArcs: Visualizing Fluctuations in Dynamic Networks

dc.contributor.authorDang, Tuan Nhonen_US
dc.contributor.authorPendar, Nicken_US
dc.contributor.authorForbes, Angus G.en_US
dc.contributor.editorKwan-Liu Ma and Giuseppe Santucci and Jarke van Wijken_US
dc.description.abstractIn this paper we introduce TimeArcs, a novel visualization technique for representing dynamic relationships between entities in a network. Force-directed layouts provide a way to highlight related entities by positioning them near to each other. Entities are brought closer to each other (forming clusters) by forces applied on nodes and connections between nodes. In many application domains, relationships between entities are not temporally stable, which means that cluster structures and cluster memberships also may vary across time. Our approach merges multiple force-directed layouts at different time points into a single comprehensive visualization that provides a big picture overview of the most significant clusters within a user-defined period of time. TimeArcs also supports a range of interactive features, such as allowing users to drill-down in order to see details about a particular cluster. To highlight the benefits of this technique, we demonstrate its application to various datasets, including the IMDB co-star network, a dataset showing conflicting evidences within biomedical literature of protein interactions, and collocated popular phrases obtained from political blogs.en_US
dc.description.sectionheadersNetworks and Graphs 1en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectH.5.2 [Information Interfaces and Presentation]en_US
dc.subjectUser Interfacesen_US
dc.subjectGraphical user interfacesen_US
dc.titleTimeArcs: Visualizing Fluctuations in Dynamic Networksen_US