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Mastering Social Media Mining with Python

You're reading from   Mastering Social Media Mining with Python Unearth deeper insight from your social media data with advanced Python techniques for acquisition and analysis

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781783552016
Length 338 pages
Edition 1st Edition
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Author (1):
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Marco Bonzanini Marco Bonzanini
Author Profile Icon Marco Bonzanini
Marco Bonzanini
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Table of Contents (10) Chapters Close

Preface 1. Social Media, Social Data, and Python FREE CHAPTER 2. #MiningTwitter – Hashtags, Topics, and Time Series 3. Users, Followers, and Communities on Twitter 4. Posts, Pages, and User Interactions on Facebook 5. Topic Analysis on Google+ 6. Questions and Answers on Stack Exchange 7. Blogs, RSS, Wikipedia, and Natural Language Processing 8. Mining All the Data! 9. Linked Data and the Semantic Web

Getting data from blogs and websites


Given the abundance of websites with interesting articles, finding textual data to mine shouldn't be a huge problem. Manually, saving one article at a time obviously doesn't scale up very well, so in this section, we will discuss some opportunities to automate the process of getting data from websites.

Firstly, we will discuss two popular free blogging services, WordPress.com and Blogger, which offer a convenient API to interact with their platform. Secondly, we will introduce the RSS and Atom web standards, used by many blogs and news publishers to broadcast their content in a format that is easy to read for a computer. Finally, we will briefly discuss more possible choices, such as connecting to Wikipedia or using web scraping as a last resort if no other option is available.

Using the WordPress.com API

WordPress.com is a blog and web hosting provider, which is powered by the open source WordPress software. The service provides free blog hosting for registered...

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