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communities     (Machine Learning Data)

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Metadata

NameCommunities and Crime
Data typesMultivariate
Data taskRegression
Attribute typesReal
Instances1994
Attributes128
Year2009
AreaSocial
DescriptionCommunities within the United States. The data combines socio-economic data from the 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crime data from the 1995 FBI UCR.

Citing the repository in published materials

If you find Network Repository useful for your research, please consider citing the following paper:

@inproceedings{nr,
     title={The Network Data Repository with Interactive Graph Analytics and Visualization},
     author={Ryan A. Rossi and Nesreen K. Ahmed},
     booktitle={Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
     url={http://networkrepository.com},
     year={2015}
}

Note that if you transform/preprocess this data for your own research, we ask that you please share the data by uploading it along with details on the transformation and reference to any published materials.

@     Name = Communities and CrimeData types = MultivariateData task = RegressionAttribute types = RealInstances = 1994Attributes = 128Year = 2009Area = SocialDescription = Communities within the United States. The data combines socio-economic data from the 1990 US Census,
law enforcement data from the 1990 US LEMAS survey, and crime data from the 1995 FBI UCR.,

Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore communities and its important node-level statistics!

  • Each point represents a node (vertex) in the graph.
  • A subset of interesting nodes may be selected and their properties may be visualized across all node-level statistics. To select a subset of nodes, hold down the left mouse button while dragging the mouse in any direction until the nodes of interest are highlighted.This feature allows users to explore and analyze various subsets of nodes and their important interesting statistics and properties to gain insights into the graph data
  • Zoom in/out on the visualization you created at any point by using the buttons below on the left.
  • Once a subset of interesting nodes are selected, the user may further analyze by selecting and drilling down on any of the interesting properties using the left menu below.
  • We also have tools for interactively visualizing, comparing, and exploring the graph-level properties and statistics.
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