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)

Chapter 3. Users, Followers, and Communities on Twitter

This chapter continues the discussion on mining Twitter data. After focusing on the analysis of tweets in the previous chapter, we will now shift our attention to the users, their connections, and their interactions.

In this chapter, we will discuss the following topics:

  • How to download a list of friends and followers for a given user
  • How to analyze connections between users, mutual friends, and so on
  • How to measure influence and engagement on Twitter
  • Clustering algorithms and how to cluster users using scikit-learn
  • Network analysis and how to use it to mine conversations on Twitter
  • How to create dynamic maps to visualize the location of tweets