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contiguous-usa     (Miscellaneous Networks)

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This network is in the collection of Miscellaneous Networks





Visualize contiguous-usa's link structure and discover valuable insights using our interactive graph visualization platform. Compare with hundreds of other networks across many different collections and types.

Metadata

NameContiguous USA
CategorySparse Networks
CollectionCU
ShortContiguous USA
Vertex typeState
Edge typeBorder
FormatUndirected
Edge weightsUnweighted
DescriptionThese are the 48 contiguous states and the District of Columbia of the United States of America (the USA). They include all states except the states of Alaska and Hawaii, which are not connected by land with the other states, and include the District of Columbia (DC). An edge denotes that two states share a border. The US states in the configuration given by this dataset exist since February 14, 1912, when Arizona was admitted as the 48th state, and is current as of 2014. The states of Alaska and Hawaii were admitted as the 49th and 50th states in 1959, but are not contiguous with the other states, and are not reflected in this dataset.

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.

Network Statistics

Nodes49
Edges107
Density0.0909864
Maximum degree8
Minimum degree1
Average degree4
Assortativity0.233397
Number of triangles171
Average number of triangles3
Maximum number of triangles8
Average clustering coefficient0.496696
Fraction of closed triangles0.406176
Maximum k-core4
Lower bound of Maximum Clique3

Data Preview

Interactive visualization of contiguous-usa's graph structure

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Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore contiguous-usa 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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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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coloring distribution

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coloring CDF

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coloring 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.)
  • We also include the CDF and CCDF distributions for each graph in the collection.
  • All visualizations and plots are zoomable. One may zoom-in or out on the data visualization using scrolling.
  • Panning. Users may also click anywhere on the plot and move the mouse in any direction to pan.
  • Adjust scale and other application dependent-parameters. All interactive visualizations may adjust the scale which is particularly important in certain types of graph data that contain highly skewed graph properties (power-lawed graphs and/or networks) such as degree distribution.

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