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Network Science with Python and NetworkX Quick Start Guide

You're reading from  Network Science with Python and NetworkX Quick Start Guide

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955316
Pages 190 pages
Edition 1st Edition
Languages
Author (1):
Edward L. Platt Edward L. Platt
Profile icon Edward L. Platt

Table of Contents (15) Chapters

Preface 1. What is a Network? 2. Working with Networks in NetworkX 3. From Data to Networks 4. Affiliation Networks 5. The Small Scale - Nodes and Centrality 6. The Big Picture - Describing Networks 7. In-Between - Communities 8. Social Networks and Going Viral 9. Simulation and Analysis 10. Networks in Space and Time 11. Visualization 12. Conclusion 13. Other Books You May Enjoy Appendix

K-cores

In the previous section, we saw that cliques often form the cores of networks and communities, but that they are computationally difficult to find. In larger networks, k-cores can be a practical alternative for finding dense regions. A k-core is created by removing all nodes of degree less than k from a network. The number k can be anything you choose. The larger k is, the more nodes will be stripped away.

The nodes that remain in a k-core are highly connected to their neighbors. However, different parts of the network might become disconnected from each other after low-degree nodes are removed. The result is that a k-core consists of islands of highly connected nodes. These islands form the core of the network (hence the name k-core). Any remaining connections can be interpreted as highly-connected backbones that join different parts of the network.

NetworkX provides...

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