ThemeRiver: Visualizing Thematic Changes in Large Document Collections
By Susan L. Havre, Elizabeth G. Hetzler, Paul D. Whitney, Lucy T. Nowell. IEEE Transactions on Visualization and Computer Graphics, 2002
809 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/5730dd763625e15a5ab703283bb305f48660f374
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Shixia Liu
- Mengchen Liu
- Yingcai Wu
- Weiwei Cui
- Xiting Wang
- Huamin Qu
- Catherine Plaisant
- Ben Shneiderman
In Computer Vision and Pattern Recognition
- Shixia Liu
- Mengchen Liu
- Yingcai Wu
- Weiwei Cui
- Ben Shneiderman
- Catherine Plaisant
- Jeffrey Heer
- Ronghua Liang
In Signal Processing
Citations in the corpus
- Visualizing time-oriented data - A systematic view (2007, methodology): “News articles (or contained keywords) can be analyzed with ThemeRiver [7], photo collections can be mapped via MyLifeBits [8], and project plans can be made comprehensible with PlanningLines [9].”
- How Hierarchical Topics Evolve in Large Text Corpora (2014, methodology): “Numerous methods [14, 42, 41] leverage a river metaphor to convey evolving topics over time.”
- Information Visualization and Visual Data Mining (2002, neutral): “2-5 in [7] ).”
- Context preserving dynamic word cloud visualization (2010, neutral): “Other related work includes stacked graphs, which are useful visualization techniques for visual analysis of quantitative variations of a set of items over time [3, 11].”
- Online Visual Analytics of Text Streams (2015, background): “For example, ThemeR-iver [19] visually depicts how keyword strengths change over time in a text corpus through a river metaphor.”
- Visualization and Visual Analysis of Multifaceted Scientific Data: A Survey (2013, neutral): “The views include histograms, scatterplot matrices [46], [50], parallel coordinates [67], [68], [69], or function graphs [70], [71], [72].”
- Protovis: A Graphical Toolkit for Visualization (2009, methodology): “The data is visualized as a stacked area chart using a ThemeRiver layout [5, 14].”