• Title Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
• Author(s) Matthew A. Russell
• Publisher: O'Reilly Media; Second Edition edition (October 22, 2013)
• Hardcover/Paperback 400 pages (est.)
• eBook HTML and PDF
• Language: English
• ISBN-10: 1449367615
• ISBN-13: 978-1449367619
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Book Description

Facebook, Twitter, LinkedIn, Google+, and other social web properties generate a wealth of valuable social data, but how can you tap into this data and discover who's connecting with whom, which insights are lurking just beneath the surface, and what people are talking about?

This book shows you how to answer these questions and many more. Each chapter combines popular and useful social web data with analysis techniques and visualization to help you find the needles in the social haystack that you've been looking for - as well as many you probably didn't even know existed.

Employ IPython Notebook and other easy to use Python packages such as the Natural Language Toolkit, NetworkX, and Matplotlib to efficiently sift through social web data as part of an experimentally-driven approach to discovering insights in social web data

• Matthew Russell, Chief Technology Officer at Digital Reasoning Systems (http://www.digitalreasoning.com/) and Principal at Zaffra (http://zaffra.com), is a computer scientist who is passionate about data mining, open source, and web application technologies. He's also the author of Dojo: The Definitive Guide (O'Reilly).

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• Data Analysis and Data Mining
• Python Programming
• Big Data
• Data Science
• Machine Learning
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