Login to your profile!



No account? sign up!

internet-as     (Technological Networks)

Download network data

This network dataset is in the category of Technological Networks



Visualize tech-internet-as'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.

@inproceedings{rossi2013topology,
     title={A Multi-Level Approach for Evaluating Internet Topology Generators},
     author={Ryan A. Rossi and Sonia Fahmy and Nilothpal Talukder},
     booktitle={Networking},
     pages={1--9},
     year={2013}
}

Network Data Statistics

Nodes40.2K
Edges85.1K
Density0.000105539
Maximum degree3.4K
Minimum degree1
Average degree4
Assortativity-0.178102
Number of triangles189.8K
Average number of triangles4
Maximum number of triangles8.5K
Average clustering coefficient0.205467
Fraction of closed triangles0.00663543
Maximum k-core24
Lower bound of Maximum Clique15

Network Data Preview

Interactive visualization of tech-internet-as's graph structure

Interactively explore the networks graph structure!

  • Use mouse wheel to zoom in/out
  • Mouseover nodes to see their degree
  • Drag network to see more details

Loading...

Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore tech-internet-as 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.
Note: You are not logged in!
Please login or join the community to leverage the many other tools and features available in our interactive graph analytics platform.

Interactive Visualization of Node-level Feature Distributions

Node-level Feature Distributions

degree distribution

Loading...

degree CDF

Loading...

degree CCDF

Loading...

kcore distribution

Loading...

kcore CDF

Loading...

kcore CCDF

Loading...

tcore distribution

Loading...

tcore CDF

Loading...

tcore CCDF

Loading...

triangle distribution

Loading...

triangle CDF

Loading...

triangle CCDF

Loading...

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.