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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

Networks in time

As we march forward toward the inevitable heat death of the universe, all things change, including networks. Networks that change in time are called dynamic networks. Network science is often concerned with how the structure of networks influences underlying systems. But, the reverse can be true as well: the processes that take place in a system can influence its network structure.

One approach to understanding how networks change over time is to look at snapshots. A snapshot is a network containing only the nodes and edges that were present at a specific point in time (like taking a picture). By taking snapshots at different times, network properties can be calculated at each point to understand how the network has evolved. One way to represent dynamic networks is to include all nodes and edges, but annotate them with the times them were present in the network...

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