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Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, Github, and Moreby Matthew A Russell
Synopses & Reviews
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 whos 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.
In this expanded and thoroughly revised second edition youll learn how to:
The book's source code is maintained in a GitHub repository maintained by the author and can be deployed as turn-key virtual machine with each chapter's source code presented in an interactive and easy to use IPython Notebook format. No complex third-party installations or advanced Python knowledge is required to get the most out of this book.
All the code and most recent updates to the code can be found at github:
How can you tap into the wealth of social web data to discover whos making connections with whom, what theyre talking about, and where theyre located? With this expanded and thoroughly revised edition, youll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.
The example code for this unique data science book is maintained in a public GitHub repository. Its designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.
Facebook, Twitter, LinkedIn, and Google+ generate a tremendous amount of valuable social data, but how can you find out whos connecting with who, what theyre talking about, what friends they have in common, or where theyre located? This book shows you how to answer these questions and more.
Youll learn how to combine social web data, analysis techniques, and visualization to help you find what youve been looking for in the social haystack—as well as useful information you didn't know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email.
In this expanded second edition youll learn how to:
All you need to get started is a programming background and a willingness to learn basic Python tools.
About the Author
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. Hes also the author of Dojo: The Definitive Guide (OReilly).
Table of Contents
Preface A Guided Tour of the Social Web Prelude Chapter 1: Mining Twitter: Exploring Trending Topics, Discovering What People Are Talking About, and More Chapter 2: Mining Facebook: Analyzing Fan Pages, Examining Friendships, and More Chapter 3: Mining LinkedIn: Faceting Job Titles, Clustering Colleagues, and More Chapter 4: Mining Google+: Computing Document Similarity, Extracting Collocations, and More Chapter 5: Mining Web Pages: Using Natural Language Processing to Understand Human Language, Summarize Blog Posts, and More Chapter 6: Mining Mailboxes: Analyzing Who's Talking to Whom About What, How Often, and More Chapter 7: Mining GitHub: Inspecting Software Collaboration Habits, Building Interest Graphs, and More Chapter 8: Mining the Semantically Marked-Up Web: Extracting Microformats, Inferencing over RDF, and More Twitter Cookbook Chapter 9: Twitter Cookbook Appendixes Information About This Book's Virtual Machine Experience OAuth Primer Python and IPython Notebook Tips and Tricks Colophon
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