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)

Collecting data from Twitter

In order to interact with the Twitter APIs, we need a Python client that implements the different calls to the API itself. There are several options as we can see from the official documentation (https://dev.twitter.com/overview/api/twitter-libraries). None of them are officially maintained by Twitter and they are backed by the open source community. While there are several options to choose from, some of them almost equivalent, so we will choose to use Tweepy here as it offers a wider support for different features and is actively maintained.

The library can be installed via pip:

$ pip install tweepy==3.3.0 

Tip

Python 3 compatibility

We're specifically installing version 3.3 of Tweepy, because of an issue with the latest version of Tweepy and Python 3, which prevents running the examples in our Python 3.4 environment. The issue was still unresolved at the time of writing, but it's likely to be fixed soon.

The first part of the interaction with the...