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Network Science with Python

You're reading from   Network Science with Python Explore the networks around us using network science, social network analysis, and machine learning

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781801073691
Length 414 pages
Edition 1st Edition
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Author (1):
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David Knickerbocker David Knickerbocker
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David Knickerbocker
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Getting Started with Natural Language Processing and Networks
2. Chapter 1: Introducing Natural Language Processing FREE CHAPTER 3. Chapter 2: Network Analysis 4. Chapter 3: Useful Python Libraries 5. Part 2: Graph Construction and Cleanup
6. Chapter 4: NLP and Network Synergy 7. Chapter 5: Even Easier Scraping! 8. Chapter 6: Graph Construction and Cleaning 9. Part 3: Network Science and Social Network Analysis
10. Chapter 7: Whole Network Analysis 11. Chapter 8: Egocentric Network Analysis 12. Chapter 9: Community Detection 13. Chapter 10: Supervised Machine Learning on Network Data 14. Chapter 11: Unsupervised Machine Learning on Network Data 15. Index 16. Other Books You May Enjoy

Investigating ego nodes and connections

In egocentric network analysis, we are interested in learning more about the communities that exist around a single node in a network. We are much less interested in the structure and makeup of the entire network. We are “zooming in,” so to speak. We will use egocentric network analysis to inspect the communities that exist around core characters from Les Miserables.

Ego 1 – Valjean

According to Wikipedia, Jean Valjean is the protagonist of Les Miserables. Knowing this, it makes sense that Valjean has the highest PageRank score of all characters in the network. The main character of any story typically interacts with more characters than anyone else, and PageRank will reflect that. For the sake of this chapter, this is as much background digging as we will do per character. If you want to do a thorough analysis of the networks that exist in a piece of literature, you should go much deeper. In this chapter, I am most...

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