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Newdle: Interactive Visual Exploration of Large Online News Collections
September/October 2010 (vol. 30 no. 5)
pp. 32-41
Jing Yang, University of North Carolina at Charlotte
Dongning Luo, University of North Carolina at Charlotte
Yujie Liu, University of North Carolina at Charlotte
Newdle is a visual-analytics system for exploring tagged online news collections. Newdle automatically constructs an article network and article-tag network for a collection and conducts clustering and path analyses on them. Using the analysis results, the system builds visualizations and supports user interaction with the networks. A topic overview lets users grasp a large collection's contents at a glance. It intuitively displays significant article clusters' semantics and temporal features in the collection. Users can also conduct in-depth analyses on topics, tags, and articles. A working prototype of Newdle uses New York Times RSS feeds as its example data input. Case studies with this prototype illustrate Newdle's effectiveness and efficiency.

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Index Terms:
Newdle, online news, RSS, visualizations, text analysis, graph, computer graphics, graphics and multimedia
Citation:
Jing Yang, Dongning Luo, Yujie Liu, "Newdle: Interactive Visual Exploration of Large Online News Collections," IEEE Computer Graphics and Applications, vol. 30, no. 5, pp. 32-41, Sept.-Oct. 2010, doi:10.1109/MCG.2010.93
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