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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 started

In the second quarter of 2015, Facebook reported nearly 1.5 billion monthly active users. In 2013, Twitter had reported a volume of 500+ million tweets per day. On a smaller scale, but certainly of interest for the readers of this book, in 2015, Stack Overflow announced that more than 10 million programming questions had been asked on their platform since the website has opened.

These numbers are just the tip of the iceberg when describing how the popularity of social media has grown exponentially with more users sharing more and more information through different platforms. This wealth of data provides unique opportunities for data mining practitioners. The purpose of this book is to guide the reader through the use of social media APIs to collect data that can be analyzed with Python tools in order to produce interesting insights on how users interact on social media.

This chapter lays the ground for an initial discussion on challenges and opportunities in social media mining and introduces some Python tools that will be used in the following chapters.

You have been reading a chapter from
Mastering Social Media Mining with Python
Published in: Jul 2016
Publisher: Packt
ISBN-13: 9781783552016
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