Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, GitHub, and more
Second Edition
Author: Matthew A Russell
Published: October 4, 2013
Publisher: O'Reilly Media
ISBN: 9781449367619
Format: Retail PDF
Reader Required: Adobe Reader, Adobe Digital Editions
This book has a support webpage, viewable code and a downloadable Vagrant VM (links in book). Tested on the above readers with no problems.
Please allow a couple seconds for the seedboxes to kick in, then it should move pretty quick.
Enjoy! :D
_______________________________________________________________________________

How can you tap into the wealth of social web data to discover whoΓÇÖs making connections with whom, what theyΓÇÖre talking about, and where theyΓÇÖre located? With this expanded and thoroughly revised edition, youΓÇÖll 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.

Employ IPython Notebook, the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites
Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data
Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects
Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit
Take advantage of more than two-dozen Twitter recipes, presented in OΓÇÖReillyΓÇÖs popular "problem/solution/discussion" cookbook format

The example code for this unique data science book is maintained in a public GitHub repository. ItΓÇÖs designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.