Python Social Media Analytics: Analyze and visualize data from Twitter, YouTube, GitHub, and more

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

About This Book

• Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, 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

Who This Book Is For

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.

What You Will Learn

• Understand the basics of social media mining
• Use PyMongo to clean, store, and access data in MongoDB
• Understand user reactions and emotion detection on Facebook
• Perform Twitter sentiment analysis and entity recognition using Python
• Analyze video and campaign performance on YouTube
• Mine popular trends on GitHub 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

In Detail

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

Table of Contents

Chapter 1. Introduction to the Latest Social Media Landscape and Importance
Chapter 2. Harnessing Social Data – Connecting, Capturing, and Cleaning
Chapter 3. Uncovering Brand Activity, Popularity, and Emotions on Facebook
Chapter 4. Analyzing Twitter Using Sentiment Analysis and Entity Recognition
Chapter 5. Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured
Chapter 6. The Next Great Technology – Trends Mining on GitHub
Chapter 7. Scraping and Extracting Conversational Topics on Internet Forums
Chapter 8. Demystifying Pinterest through Network Analysis of Users Interests
Chapter 9. Social Data Analytics at Scale – Spark and Amazon Web Services