Bonzanini Mastering Social Media Mining with Python 2016

Bonzanini Mastering Social Media Mining with Python 2016

Bonzanini Mastering Social Media Mining with Python 2016
pdf | 11.17 MB | English | Isbn:B01BFD2Z2Q |
Author: Marco Bonzanini | PAge: 333 | Year: 2016


Key Features

  • Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide
  • Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data
  • This is your one-stop solution to fetching, storing, analyzing, and visualizing social media data

Book Description
Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights.
This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data.

What you will learn

  • Interact with a social media platform via their public API with Python
  • Store social data in a convenient format for data analysis
  • Slice and dice social data using Python tools for data science
  • Apply text analytics techniques to understand what people are talking about on social media
  • Apply advanced statistical and analytical techniques to produce useful insights from data
  • Build beautiful visualizations with web technologies to explore data and present data products

About the Author
Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a PhD in information retrieval from Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems.
He maintains a personal blog at, where he discusses different technical topics, mainly around Python, text analytics, and data science.
When not working on Python projects, he likes to engage with the community at PyData conferences and meet-ups, and he also enjoys brewing homemade beer.

Table of Contents

  • Social Media, Social Data, and Python
  • #MiningTwitter – Hashtags, Topics, and Time Series
  • Users, Followers, and Communities on Twitter
  • Posts, Pages, and User Interactions on Facebook
  • Topic Analysis on Google+
  • Questions and Answers on Stack Exchange
  • Blogs, RSS, Wikipedia, and Natural Language Processing
  • Mining All the Data!
  • Linked Data and the Semantic Web

Category:Data Mining, Data Modeling & Design, Python Computer Programming

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