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 analysis

We have seen so far that the GitHub API provides interesting sets of information about the code repositories and metadata around the activity of its users around these repositories. In the following sections, we will analyze this data to find out which are the most popular repositories through the analysis of its descriptions and then drilling down to the watchers, forks, and issues submitted on the emerging technologies. Since, technology is evolving so rapidly, this approach could help us to stay on top of the latest trending technologies.

In order to find out what are the trending technologies, we will perform the analysis in a few steps:

  • Detect the most trending topics/technologies based on descriptions
  • Identify the most popular programming languages globally
  • Find out what programming languages are used for the top technologies
  • What are the differences between technologies in terms of repository size, open issues, number of forks, and watchers
  • See what are the most popular projects...