Book Image

Mastering Social Media Mining with Python

By : Marco Bonzanini
Book Image

Mastering Social Media Mining with Python

By: Marco Bonzanini

Overview of this book

Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights. This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data.
Table of Contents (10 chapters)

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.