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Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More by [Russell, Matthew A.]
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Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More 2nd Edition, Kindle Edition

3.9 out of 5 stars 4 customer reviews

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Product description

Review

Mining the social web, again
When we first published "Mining the Social Web," I thought it was one of the most important books I worked on that year. Now that we're publishing a second edition (which I didn't work on), I find that I agree with myself. With this new edition, "Mining the Social Web" is more important than ever.
While we're seeing more and more cynicism about the value of data, and particularly "big data," that cynicism isn't shared by most people who actually work with data. Data has undoubtedly been overhyped and oversold, but the best way to arm yourself against the hype machine is to start working with data yourself, to find out what you can and can't learn. And there's no shortage of data around. Everything we do leaves a cloud of data behind it: Twitter, Facebook, Google+ -- to say nothing of the thousands of other social sites out there, such as Pinterest, Yelp, Foursquare, you name it. Google is doing a great job of mining your data for value. Why shouldn't you?
There are few better ways to learn about mining social data than by starting with Twitter; Twitter is really a ready-made laboratory for the new data scientist. And this book is without a doubt the best and most thorough approach to mining Twitter data out there. But that's only a starting point. We hear a lot in the press about sentiment analysis and mining unstructured text data; this book shows you how to do it. If you need to mine the data in web pages or email archives, this book shows you how. And if you want to understand how to people collaborate on projects, "Mining the Social Web" is the only place I've seen that analyzes GitHub data.
All of the examples in the book are available on Github. In addition to the example code, which is bundled into IPython notebooks, Matthew has provided a VirtualBox VM that installs Python, all the libraries you need to run the examples, the examples themselves, and an IPython server. Checking out the examples isr

Book Description

Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

Product details

  • Format: Kindle Edition
  • File Size: 9504.0 KB
  • Print Length: 448 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 2 edition (4 Oct. 2013)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B00FNBWNLU
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Not Enabled
  • Average Customer Review: 3.9 out of 5 stars 4 customer reviews
  • Amazon Bestsellers Rank: #467,205 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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VINE VOICE
8 September 2017
Format: Kindle Edition|Verified Purchase
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18 January 2018
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20 November 2013
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21 December 2013
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Most helpful customer reviews on Amazon.com

Amazon.com: 4.3 out of 5 stars 64 reviews
chungking
5.0 out of 5 starsCan't imagine a better organized resource
26 November 2014 - Published on Amazon.com
Format: Paperback|Verified Purchase
6 people found this helpful.
Brendon Unland
5.0 out of 5 starsNew Standard in Technical Books
8 November 2013 - Published on Amazon.com
Format: Paperback|Verified Purchase
21 people found this helpful.
Ted Chao
4.0 out of 5 starsUseful and good reference for methodology of social media mining
13 March 2014 - Published on Amazon.com
Format: Kindle Edition|Verified Purchase
3 people found this helpful.
Leu_V1
3.0 out of 5 starsLooks good so far
8 May 2014 - Published on Amazon.com
Format: Paperback|Verified Purchase
5 people found this helpful.
JGB_LAX
3.0 out of 5 starsOverall a good resource. Gave me enough of a background that ...
29 November 2014 - Published on Amazon.com
Format: Paperback|Verified Purchase
One person found this helpful.
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