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Mining the social web

By: Material type: TextTextPublication details: New Delhi O'Reilly, ©2011.Description: xx, 332 p. : ill. ; 24 cmISBN:
  • 1449388345
  • 9789350232941
Other title:
  • Mining the social web : analyzing data from Facebook, Twitter, LinkedIn, and other social media sites [Cover title]
Subject(s): DDC classification:
  • 006.312 22 RUS-M
LOC classification:
  • QA76.9.D343 R87 2011
Online resources:
Contents:
Introduction : hacking on Twitter data -- Microformats : semantic markup and common sense collide -- Mailboxes : oldies but goodies -- Twitter : friends, followers, and setwise operations -- Twitter : the tweet, the whole tweet, and nothing but the tweet -- LinkedIn : clustering your professional network for fun (and profit?) -- Google buzz : TF-IDF, cosine similarity, and collocations -- Blogs et al. : natural language processing (and beyond) -- Facebook : the all-in-one wonder -- The semantic web : a cocktail discussion.
Summary: Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This book shows you how to answer these questions and more. Each chapter introduces techniques for mining data in different areas of the social web, including blogs and email.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Books Books IIITD General Stacks Computer Science and Engineering 006.312 RUS-M (Browse shelf(Opens below)) Available G00035
Books Books IIITD Reference Computer Science and Engineering REF 006.312 RUS-M (Browse shelf(Opens below)) Available 001462
Total holds: 0

Includes index.

Introduction : hacking on Twitter data -- Microformats : semantic markup and common sense collide -- Mailboxes : oldies but goodies -- Twitter : friends, followers, and setwise operations -- Twitter : the tweet, the whole tweet, and nothing but the tweet -- LinkedIn : clustering your professional network for fun (and profit?) -- Google buzz : TF-IDF, cosine similarity, and collocations -- Blogs et al. : natural language processing (and beyond) -- Facebook : the all-in-one wonder -- The semantic web : a cocktail discussion.

Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This book shows you how to answer these questions and more. Each chapter introduces techniques for mining data in different areas of the social web, including blogs and email.

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