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

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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 sitesApply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language dataBootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projectsBuild interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkitTake 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

  • File Size: 9504 KB
  • Print Length: 448 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: O’Reilly Media; 2 edition (October 4, 2013)
  • Publication Date: October 4, 2013
  • Sold by:  Amazon Digital Services LLC
  • Language: English
  • Text-to-Speech: Enabled
  • X-Ray: Enabled
  • Word Wise: Not Enabled
  • Lending: Not Enabled
  • Enhanced Typesetting: Not Enabled

Customer Reviews

Can’t imagine a better organized resource

 on November 26, 2014
By chungking
This is more than a “book” – it is a course, and a very well thought through, well supported course at that.

The Book Re-Imagineered – and hands-on tech for the Non-Techie.

 on April 3, 2018
By Orange Monkey
AMAZING book – and as you can understand from other reviews, it’s an re-imagineered idea of a ‘book’. I won’t reiterate as it’s covered by other reviewers.

New Standard in Technical Books

 on November 7, 2013
By Brendon Unland
I have purchased just about every book available on social media data mining/ analytics, including the first edition of this book. What Matthew Russell has done with this second edition is amazing. With the purchase of this book, you get a fully functional virtual machine (available via download on GitHub.) As updates are made to the code for the book, you can easily pull them from GitHub. This eliminates the countless hours you spend downloading, configuring, troubleshooting, wondering if you got the right version of the needed software, etc. Within minutes you can read the book and type the code samples. Actually, the code is already there, you simply enter in some key values and watch the code run. You can then morph the code and see the effects of your changes.

Great reference and clear, useful examples

 on November 8, 2014
By k polich
This is a great tour of the APIs provided by some of the larger social platforms, and helpful commentary about some of the data munging and analysis steps required to do something interesting. The clear and easy to follow examples are further enhanced through the accompanying virtual machine of the book, allowing you to escape the headache of installing, configuring, and selecting the right version of all the supporting software and libraries.

but it would have been good to know that it’s non-trivial to set up the …

 on September 3, 2014
By Phil Wheat
I’m just getting started, but it would have been good to know that it’s non-trivial to set up the dev environment and that the Virtual Machine requires Oracle’s VirtualBox which is incompatible (cannot be installed on the same computer) with the VM system I use (Hyper-V). It looks like the content is good, but it also seems like it will take some work to get started on it.

Useful and good reference for methodology of social media mining

 on March 13, 2014
By Ted Chao
I am quite surprised about the way this book presenting how to do text mining on social media. Those social media with different data format bundled with both structure and unstructured data is hard to process by a common way of text mining. But, with lots of practical source code and example, it makes quite easy for a beginner to comprehend much more detail.

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