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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? 2. Working with Networks in NetworkX FREE CHAPTER 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

Summary

This chapter introduced affiliation networks and the tools provided by NetworkX for working with affiliation networks, with special attention to using projections to create co-affiliation networks. Affiliation networks are ubiquitous in network data. Whenever there is a symmetrical relationship that can connect more than two things, there is an underlying affiliation structure. Many single-mode networks are really co-affiliation networks—projections of affiliation networks onto one type of node. Different projections have different interpretations, such as the number of paths or similarities. Choosing an appropriate projection for the data and for the question being asked can reveal important properties of a network that might otherwise be overlooked. Even as you encounter standard single-mode networks in the rest of this book, and in real-world data, it is often...

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