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
About the Authors
About the Reviewer
Customer Feedback

Data pull

We start the analysis by selecting the channel and the video. For the purpose of this chapter we select the Sony PlayStation YouTube channel, as it is one of the most popular brands in the entertainment sector. We find its URL by performing a search on the YouTube search engine and get a result similar to the following:

The ID of the channel corresponds to the last element of the URL, which in this case is UC-2Y8dQb0S6DtpxNgAKoJKA.

In the first place, we will extract the videos with the most views to understand what kind of videos gather most interest from users. In order to perform this task we have to define two functions:

  • get_channel_videos(): A function to list all the videos associated with the channel
  • get_statistics(): A function that collects statistics (number of views, likes, dislikes) for a single video

It is required to split this part in two steps as there is no endpoint that retrieves all the videos for a channel...