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

Getting the data

Forums do not provide programmatic interfaces (APIs) to capture data. However, you can connect to the website as a user to see all the conversations and collect data. The process of data extraction automatically from websites is called 'web scraping'.

Introduction to scraping

Since the beginning of the web, web scraping has been the main challenge for anyone who wanted to exploit the richness of information available on the Internet. In the very beginning, very few APIs were available and people used to copy the content of websites by just using copy-paste schema. Then, some programmatic tools were created to follow links (crawling) and extract the content from web pages (scraping). The information was structured by using text patterns (regex) or DOM (Document Object Model) parsing methods. More recently, the development of semantic analysis tools and artificial intelligence enabled alternative approaches, which are much more efficient and closer to human understanding and...