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Issue No.05 - September/October (2010 vol.30)
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
ABSTRACT
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.
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, September/October 2010, doi:10.1109/MCG.2010.93
REFERENCES
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3. F. Viégas, M. Wattenberg, and J. Feinberg, "Participatory Visualization with Wordle," IEEE Trans. Visualization and Computer Graphics, vol. 15, no. 6, 2009, pp. 1137–1144.
4. S.E. Schaeffer, "Graph Clustering," Computer Science Rev., vol. 1, no. 1, 2007, pp. 27–64.
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