Siddhartha Chatterjee & Michal Krystyanczuk 
Python Social Media Analytics [EPUB ebook] 

Leverage the power of Python to collect, process, and mine deep insights from social media data

• Acquire data from various social media platforms such as Facebook, Twitter, You Tube, Git Hub, and more


• Analyze and extract actionable insights from your social data using various Python tools


• A highly practical guide to conducting efficient social media analytics at scale

If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process.

• Understand the basics of social media mining


• Use Py Mongo to clean, store, and access data in Mongo DB


• Understand user reactions and emotion detection on Facebook


• Perform Twitter sentiment analysis and entity recognition using Python


• Analyze video and campaign performance on You Tube


• Mine popular trends on Git Hub and predict the next big technology


• Extract conversational topics on public internet forums


• Analyze user interests on Pinterest


• Perform large-scale social media analytics on the cloud

Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and You Tube 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, You Tube, 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 Mongo DB using Py Mongo. 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.

This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.