Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

by Matthew A. Russell

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Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More by Matthew A. Russell

How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll 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 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 O’Reilly’s popular "problem/solution/discussion" cookbook format

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

Product Details

ISBN-13: 9781449367619
Publisher: O'Reilly Media, Incorporated
Publication date: 10/17/2013
Edition description: Second Edition
Pages: 448
Sales rank: 709,740
Product dimensions: 7.00(w) x 9.20(h) x 1.20(d)

About the Author

Matthew Russell, Chief Technology Officer at Digital Reasoning, Principal at Zaffra, and author of several books on technology including Mining the Social Web (O'Reilly, 2013), now in its second edition. He is passionate about open source software development, data mining, and creating technology to amplify human intelligence. Matthew studied computer science and jumped out of airplanes at the United States Air Force Academy. When not solving hard problems, he enjoys practicing Bikram Hot Yoga, CrossFitting and participating in triathlons.

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 & Tricks

  • Colophon

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