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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

Even Easier Scraping!

In the previous chapter, we covered the basics of web scraping, which is the act of harvesting data from the web for your uses and projects. In this chapter, we will explore even easier approaches to web scraping and will also introduce you to social media scraping. The previous chapter was very long, as we had a lot to cover, from defining scraping to explaining how the Natural Language Toolkit (NLTK), the Requests library, and BeautifulSoup can be used to collect web data. I will show simpler approaches to getting useful text data with less cleaning involved. Keep in mind that these easier ways do not necessarily replace what was explained in the previous chapter. When working with data or in software projects and things do not immediately work out, it is useful to have options. But for now, we’re going to push forward with a simpler approach to scraping web content, as well as giving an introduction to scraping social media text.

First, we will cover...

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Network Science with Python
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