Book Image

Python Social Media Analytics

By : Baihaqi Siregar, Siddhartha Chatterjee, Michal Krystyanczuk
Book Image

Python Social Media Analytics

By: Baihaqi Siregar, Siddhartha Chatterjee, Michal Krystyanczuk

Overview of this book

Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Summary


YouTube has emerged as the most preferred platform for video viewing, going ahead of television. This popularity has resulted in astronomical amounts of video hours being uploaded and viewed every hour. Due to its popularity, YouTube was acquired by Google in 2006. Since then, it has become a de facto place for companies to upload promotional videos for its consumers and fans. The significant advantage YouTube provides over TV is in the ability to precisely analyze the impact of the video on the viewers. We do this through data accessed by its API like, number of views, likes, and dislikes. YouTube also allows its users to express their views on the videos by commenting displayed under the videos. This piece of information is extremely interesting to measure the response of video audience. All the data on users is a goldmine for media analysts to understand user behavior.

In this chapter, we accessed all publicly available data using the Google Data API. We chose the Sony PlayStation...