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misc-Reuters911     (Miscellaneous Networks)

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This network is in the collection of Miscellaneous Networks





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Metadata

CategorySparse Networks
CollectionMisc. Networks
Tags
ShortWord co-occurences
Vertex typeWords
Edge typeCo-occur
FormatUndirected
Edge weightsWeighted
DescriptionReuters news, Sept 11 to Nov 15, 2001. The Reuters terror news network is based on all stories released during 66 consecutive days by the news agency Reuters concerning the September 11 attack on the U.S., beginning at 9:00 AM EST 9/11/01. The vertices of a network are words (terms); there is an edge between two words iff they appear in the same text unit (sentence). The weight of an edge is its frequency and there are no self-loops.

Please cite the following if you use the data:

@inproceedings{nr,
     title={The Network Data Repository with Interactive Graph Analytics and Visualization},
     author={Ryan A. Rossi and Nesreen K. Ahmed},
     booktitle={AAAI},
     url={http://networkrepository.com},
     year={2015}
}

Note that if you transform/preprocess the data, please consider sharing the data by uploading it along with the details on the transformation and reference to any published materials using it.

@article{corman2002studying,
     title={Studying Complex Discursive Systems.},
     author={Corman, Steven R and Kuhn, Timothy and McPhee, Robert D and Dooley, Kevin J},
     journal={Human communication research},
     volume={28},
     number={2},
     pages={157--206},
     year={2002},
     publisher={Wiley Online Library}
}

Network Statistics

Nodes13.3K
Edges148K
Density0.00166589
Maximum degree2.3K
Minimum degree0
Average degree22
Assortativity-0.108979
Number of triangles3.5M
Average number of triangles263
Maximum number of triangles69.8K
Average clustering coefficient0.367984
Fraction of closed triangles0.106933
Maximum k-core74
Lower bound of Maximum Clique25

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Interactive visualization of misc-Reuters911's graph structure

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Interactive Visualization of Node-level Properties and Statistics

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Interactive Visualization of Node-level Feature Distributions

Node-level Feature Distributions

degree distribution

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degree CDF

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degree CCDF

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kcore distribution

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kcore CDF

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kcore CCDF

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triangle distribution

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triangle CDF

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triangle CCDF

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All visualizations and analytics are interactive and flexible for exploratory analysis and data mining in real-time and include the following features:

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