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


Conventional social media such as Facebook and Twitter with user-generated content are an interesting way to analyze information about individuals and organizations. The APIs of these platforms are useful to gather and analyse a lot of this data emanating from these platforms. on the other hand, online forums without structured freely available APIs provide a great sources of topical discussions. The main difference is mostly the anonymous nature of the forums, which encourages individuals to have long and deep discussions on various topics (technology, politics, culture, and so on), unlike on other social media where one is often identified through pseudonyms and actual identifiers. These millions of rich conversations on Internet forums have become extremely interesting for companies to learn about the trends of their consumers.

To harness conversational data, we explored the techniques to create crawlers using the Scrappy framework. After extraction and storage of this data, we...