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 (15 chapters)
Mastering Social Media Mining with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Summary


In this chapter, we looked at the Google+ API. We also discussed how to register a project on the Google Developer Console and how to enable the desired API(s) for our project.

The chapter started with an example that showed how to perform a search using the Google+ API. The discussion was then built upon this example in order to embed the use of the API in a web application. Taking advantage of Flask, a micro framework for web development that allows to get up and running with a few lines of code, we built a web GUI to show the results of a search session.

The next step was to analyze textual notes from a user or page. After downloading the user activities and storing them in the JSON Lines format, we discussed a few details of TF-IDF as a statistical approach to extract interesting keywords from a piece of text.

In the next chapter, we will move our attention to the field of question answering, and we will do so by approaching the Stack Overflow API.