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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

Modeling your data

When representing data as a network, there are many decisions to make along the way. Different types of networks are helpful for understanding different types of data and for asking different types of questions. This section will take a closer look at some of the important considerations.

When creating a network from data, one of the most important questions to consider is what exactly the nodes and edges should represent. Often there are many possibilities, even for the same dataset. Any particular choice focuses on some aspects of the data, possibly discarding others. Networks are fundamentally about relationships and connections, so one way to define nodes and edges is to think about what types of relationships you're interested in. Some possibilities include the following:

  • Social relationships, such as friendships, romantic relationships, or even rivalries...
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