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ia-wikiquote-user-edits     (Interaction Networks)

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This network is in the collection of Interaction Networks





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Metadata

CategorySparse Networks
CollectionInteraction Networks
Tags
ShortWikiquote user-article edit network
Vertex typeUser, article
Edge typeEdit
FormatBipartite
Edge weightsMultigraph, unweighted
MetadataTime
DescriptionA bipartite edit network of the English Wikipedia. It contains users and pages from the English Wikipedia, connected by edit events. Each edge represents an edit. The dataset includes the timestamp of each edit. Third column is the edge weight and fourth column is the edge timestamp.

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={https://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.

@misc{dumpsWikimedia,
     author = {Wikimedia Foundation},
     title = {Wikimedia Downloads},
     month = {January},
     year = {2010},
     howpublished = {\url{http://dumps.wikimedia.org/}
}}

Network Statistics

Nodes93.4K
Edges549.1K
Density0.000125776
Maximum degree50.3K
Minimum degree1
Average degree11
Assortativity0.945858
Number of triangles65.5M
Average number of triangles700
Maximum number of triangles7.5M
Average clustering coefficient0.546276
Fraction of closed triangles0.0188248
Maximum k-core2.4K
Lower bound of Maximum Clique77

Data Preview

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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:

  • Degree, k-core, triangles, and triangle-core distributions. We include plots for each of the fundamental graph features and counts of the number with a particular property (i.e., number of nodes that form k triangles or have degree k, etc.)
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