Mining the social web

Author(s)

    • Russell, Matthew A. (Computer scientist)

Bibliographic Information

Mining the social web

Matthew A. Russell

O'Reilly, 2013.10

2nd ed

Other Title

Data mining Facebook, Twitter, Linkedin, Google+, Github, and more

Available at  / 4 libraries

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Note

Previous edition: 2011

Includes index

Description and Table of Contents

Description

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 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 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.

by "Nielsen BookData"

Details

  • NCID
    BB15656120
  • ISBN
    • 9781449367619
  • Country Code
    cc
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Beijing ; Tokyo
  • Pages/Volumes
    xxiv, 421 p.
  • Size
    24 cm
  • Classification
  • Subject Headings
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