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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
Author Profile Icon David Knickerbocker
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

Identifying other research opportunities

When doing any kind of network analysis, it is important to know that there is always more that you can do; for instance, we could do the following:

  • We could embed additional information into the graph, such as weights or node types (teacher, student, revolutionary, and so on)
  • We could color nodes by node type for easier identification of communities
  • We could size nodes by the number of degrees or the centrality score to make it easier to identify important nodes
  • We could use directed networks to understand the directionality of information sharing

There is always more that you can do, but it is important to know that enough is enough. You should use what you need. For this chapter, I originally got stuck trying to do too much, and I lost time trying to figure out how to do things that weren’t actually all that important to teaching this topic. Keep it simple and add only what you need and what is helpful. Add...

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