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what is it
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netzen is a software tool for the analysis and visualization of social and other scale-free networks.
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features
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netzen provides integrated visualization of node-link diagrams with scatterplots, parallel views and other visualizations of node and edge properties, including centrality metrics such as closeness, betweenness, eigenvector and Markov centralities.
netzen also incorporates sensitivity analysis and uncertainty evaluation of diverse graph metrics.
What's more, netzen provides unprecedented flexibility to layout and customize views for presentation-ready visualization.
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source
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netzen code is now hosted in Google code. Please follow this link for instructions on how to download the latest code via svn:
http://code.google.com/p/netzen/
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download
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Netzen v 1.0 netzen-src.1.0.tar.gz (beta). Includes:
- Flow-based scatterplots
- Sensitivity views
- Centrality and sensitivity layouts for social networks
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Download (older) source code here (v 0.1)
Download (older) source code here (v 0.11)
It has been compiled successfully on linux (fedora), MAC OS X, and Windows under msys.
You will need the following libraries:
Download example data here
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examples
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Long-term probabilities of landing at a square in Monopoly.
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contribute
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We are looking for contributors to extend netzen in the following areas:
- Novel Visualizations
- Network analysis metrics
- Graph layouts
- Scalability
If interested, please send us an email at:
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publications
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Flow-based Scatterplots for Sensitivity Analysis
Yu-Hsuan Chan, Carlos D. Correa and Kwan-Liu Ma. Proc. IEEE Symposium on Visual Analytics Science and Technology 2010.
[PDF]
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Social Network Discovery based on Sensitivity Analysis.
Tarik Crnovrsanin, Carlos D. Correa and Kwan-Liu Ma.
Proc. Intl. Conf. Advances in Social Networks Analysis and Mining (ASONAM 2009), Athens, Greece, July 2009.
[PDF]
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A Framework for Uncertainty-Aware Visual Analytics.
Carlos D. Correa, Yu-Hsuan Chan and Kwan-Liu Ma. Proc. IEEE Symposium on Visual Analytics Science and Technology 2009.
[PDF]
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Follow us on twitter.
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Acknowledgments
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NetZen is made available through the projects supported by the National Science Foundation
through grants CCF-0808896 and CCF-1025269.
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