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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 Explore and visualize network data effectively

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955316
Length 190 pages
Edition 1st Edition
Languages
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Author (1):
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Edward L. Platt Edward L. Platt
Author Profile Icon Edward L. Platt
Edward L. Platt
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Table of Contents (15) Chapters Close

Preface 1. What is a Network? FREE CHAPTER 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

Cliques

In the densest neighborhoods of a network, it is sometimes possible to find groups of nodes that are all connected to each other. Such groups are called cliques. Identification of cliques is another way to analyze the medium-scale structure of a network. Because cliques are highly interconnected, the nodes in a clique rarely belong to different communities. In fact, cliques often form the cores of communities.

Chapter 4, Affiliation Networks, described how to transform an affiliation network into a single-mode network using projections. For each node removed by such projections, its neighbors are connected into a clique. Cliques can give clues to an underlying affiliation network structure.

NetworkX provides the find_cliques() function to find cliques in a network. This function returns an iterator over all cliques in an arbitrary order. For example, using this function...

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