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:
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.
@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}
}
Network Data Statistics
| Nodes | 999.9K |
| Edges | 5M |
| Density | 1.00037e-05 |
| Maximum degree | 27 |
| Minimum degree | 1 |
| Average degree | 10 |
| Assortativity | 0.000265159 |
| Number of triangles | 513 |
| Average number of triangles | 0 |
| Maximum number of triangles | 2 |
| Average clustering coefficient | 1.03028e-05 |
| Fraction of closed triangles | 1.02527e-05 |
| Maximum k-core | 8 |
| Lower bound of Maximum Clique | 3 |
Network Data Preview
Interactive visualization of ER-AvgDeg10-1M-L5's graph structure
Interactively explore the networks 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
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- We also have tools for interactively visualizing, comparing, and exploring the graph-level properties and statistics.
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