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

Mining geo coordinates


As previously described, geo and h-geo are microformats for publishing geographical information. While reading a book about social media, one may ask whether geographical metadata falls into the description of social data. When thinking about geodata, the core idea to keep in mind is that geographical information can be exploited in so many applications. For example, users may want to perform a location-specific search for businesses (as in Yelp) or find pictures taken from a particular location. More in general, everybody is physically located somewhere or is looking for something physically located somewhere. Geographical metadata enables applications to fulfill the need for location-specific customizations. In the age of social and mobile data, these customizations open many new horizons for application developers.

Back to our journey through semantically marked up data, this section describes how to extract geographical metadata from web pages using Wikipedia for...