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.

Python Social Media Analytics
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Python Social Media Analytics
By:
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 (10 chapters)
Preface
Introduction to the Latest Social Media Landscape and Importance
Harnessing Social Data - Connecting, Capturing, and Cleaning
Uncovering Brand Activity, Popularity, and Emotions on Facebook
Analyzing Twitter Using Sentiment Analysis and Entity Recognition
Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured
The Next Great Technology – Trends Mining on GitHub
Scraping and Extracting Conversational Topics on Internet Forums
Demystifying Pinterest through Network Analysis of Users Interests
Social Data Analytics at Scale – Spark and Amazon Web Services
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