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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

Summary

This chapter discussed some more options to mine data on social media. Beyond the usual popular social networks, such as Twitter, Facebook, and Google+, many other platforms offer APIs to access their data.

When a Python client is not available for a particular platform, we can implement a custom client, exploiting the simplicity of the requests library. The implementation of a custom client seems to add unnecessary complexity at first, but it provides an important layer of abstraction that pays off in terms of design in the long run.

Besides the instructions for a custom client implementation, we also examined some other popular services to mine complex objects. We retrieved data about videos from YouTube, open source projects from GitHub, and local businesses such as restaurants from Yelp.

Many more social media platforms remain unexplored in this book, because providing a comprehensive discussion would be unrealistic, but I hope that the readers have a good taste of the many possibilities...

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