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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 has described many different techniques for quantifying the large-scale structure of networks. Network size can be quantified using the diameter or mean shortest path. Global clustering can be used to quantify how likely a node's neighbors are to be neighbors with each other. Connectivity measures, such as the minimum or average node/edge connectivity, are calculated by finding minimum cuts, and quantify network resilience. The chapter concluded by showing how inequality measures such as entropy and the Gini index can be used to turn small-scale centrality measures into large-scale measures of network centralization. The next chapter discusses medium-scale network structures and community detection.

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