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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

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955316
Pages 190 pages
Edition 1st Edition
Languages
Author (1):
Edward L. Platt Edward L. Platt
Profile icon Edward L. Platt

Table of Contents (15) Chapters

Preface 1. What is a Network? 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

Summary

This chapter has shown us how simulations can be used to better understand both the processes that create network structure and the processes that are influenced by network structure. The Watts-Strogatz model creates small-world networks by adding random shortcuts to a highly-clustered ring network. Preferential attachment creates heavy-tailed, scale-free networks, where a few nodes have most of the connections. Configuration models are used to construct synthetic networks with properties similar to real networks. Finally, this chapter showed how agent-based modeling can be used to simulate a social learning process occurring on an existing network structure. In the next chapter, you'll learn about working with data that represents objects in space or time.

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