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Mastering Social Media Mining with Python

Python programiranje Python programiranje

Mastering Social Media Mining with Python

Autor: Marco Bonzanini
Broj strana: 338
ISBN broj: 9781783552016
Godina izdanja: 2016.

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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

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.


Marco Bonzanini

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

Chapter 1: Social Media, Social Data, and Python
Chapter 2: #MiningTwitter – Hashtags, Topics, and Time Series
Chapter 3: Users, Followers, and Communities on Twitter
Chapter 4: Posts, Pages, and User Interactions on Facebook
Chapter 5: Topic Analysis on Google+
Chapter 6: Questions and Answers on Stack Exchange
Chapter 7: Blogs, RSS, Wikipedia, and Natural Language Processing
Chapter 8: Mining All the Data!
Chapter 9: Linked Data and the Semantic Web


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