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  • Book Overview & Buying Network Science with Python
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Network Science with Python

Network Science with Python

By : David Knickerbocker
5 (15)
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Network Science with Python

Network Science with Python

5 (15)
By: David Knickerbocker

Overview of this book

Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.
Table of Contents (17 chapters)
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1
Part 1: Getting Started with Natural Language Processing and Networks
5
Part 2: Graph Construction and Cleanup
9
Part 3: Network Science and Social Network Analysis

Graph Construction and Cleaning

We have covered quite a lot of ground up to this point. In the previous chapters, we introduced NLP, network science, and social network analysis, and we learned how to convert raw text into network data. We even visualized a few of these networks. I hope that seeing text converted into a visualized network had the same impact on you as it did on me. The first time I attempted this, I used the book of Genesis, from the Bible, and being able to convert text from thousands of years ago into an actual interactive network took my breath away.

In the previous two chapters, we learned a few different ways to collect text data from websites and social networks on the internet and to use that text data to create networks. The good news is that I don’t need to show you more ways to scrape text. You have enough options, and you should be able to use this knowledge as a foundation for other kinds of scraping.

The bad news is that it is time to get...

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Programming languages
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Network Science with Python
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