| Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites |  | Author: Matthew A. Russell Publisher: O'Reilly Media Category: Book
List Price: $39.99 Buy New: $22.67 as of 5/27/2012 09:25 EDT details You Save: $17.32 (43%)
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Seller: new_books_today Sales Rank: 12,098
Languages: English (Unknown), English (Original Language), English (Published) Media: Paperback Edition: 1 Pages: 356 Number Of Items: 1 Shipping Weight (lbs): 1.3 Dimensions (in): 9.3 x 7 x 0.8
ISBN: 1449388345 EAN: 9781449388348 ASIN: 1449388345
Publication Date: February 8, 2011 Availability: Usually ships in 1-2 business days
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| • | ISBN13: 9781449388348 | | • | Condition: New | | • | Notes: BRAND NEW FROM PUBLISHER! 100% Satisfaction Guarantee. Tracking provided on most orders. Buy with Confidence! Millions of books sold! |
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Product Description
Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s making connections with social media, what they’re talking about, and where they’re located. You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve 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. All you need to get started is a programming background and a willingness to learn basic Python tools. - Get a straightforward synopsis of the social web landscape
- Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+
- Learn how to employ easy-to-use Python tools to slice and dice the data you collect
- Explore social connections in microformats with the XHTML Friends Network
- Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection
- Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits
"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google
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