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)

Users, friends, and followers


One of the main differences between Twitter and other popular social networks is the way users can connect. Relationships on Twitter are, in fact, not necessarily bidirectional. A user can choose to subscribe to other users' tweets, becoming their follower, but the act of following might not be reciprocated. This is very different from what happens with other social networks such as Facebook and LinkedIn, where the relationship has to be confirmed by both parties before taking place.

Using the Twitter terminology, the two directions of the relationship (people I follow versus the people who follow me) have different names. The people I follow are referred to as friends, while the people who follow me are referred to as my followers. When the relationship is bidirectional, the user is commonly described as a mutual friend.

Back to the Twitter API

The Twitter API provides several endpoints to retrieve information about followers, friends, and user profiles in general...