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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

Projections

While affiliation networks are useful for representing the full structure of many-to-many relationships, it is sometimes easier to work with standard single-mode networks. This might be the case if an analysis focuses on a particular type of node, or if a necessary technique is only available for single-mode networks, or if the affiliation network has too many nodes to visualize clearly. Luckily, it is possible to create single-mode networks out of an affiliation network using a process called projection. And, as you might expect, NetworkX makes it easy.

Single-mode networks built from affiliation networks are called co-affiliation networks, because the nodes are connected by an edge if they have common affiliations. There are several types of projections that are used to create co-affiliation networks, but they all revolve around the same idea: connecting nodes with...

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