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ER-AvgDeg10-1M-L5     (Labeled Networks)

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This network dataset is in the category of Labeled Networks



Visualize ER-AvgDeg10-1M-L5's link structure and discover valuable insights using the interactive network data visualization and analytics platform. Compare with hundreds of other network data sets across many different categories and domains.

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 Data Statistics

Nodes999.9K
Edges5M
Density1.00037e-05
Maximum degree27
Minimum degree1
Average degree10
Assortativity0.000265159
Number of triangles513
Average number of triangles0
Maximum number of triangles2
Average clustering coefficient1.03028e-05
Fraction of closed triangles1.02527e-05
Maximum k-core8
Lower bound of Maximum Clique3

Network Data Preview

Interactive visualization of ER-AvgDeg10-1M-L5'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 ER-AvgDeg10-1M-L5 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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