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

Scope and process

The project and analysis in the chapter will cover the data gathered from the Twitter feeds through the Twitter API. Working with the API, the user has a selection of different endpoints (functionalities). We will focus on two of the most popular: the streaming and the search endpoints (REST API). The first one gives access to real-time data, showing tweets as they are published (in fact the access is to the sample, not all tweets). The latter allows to query historical tweets (up to about a week), based on several criteria, which is more suitable for a static analysis. The following are the steps to gather the data from the Twitter feeds:

  • Getting the data
  • Data pull
  • Data cleaning

Let us take a look at each one in detail.