Free Ebook Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, Github, And More

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Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, Github, And More

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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

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Book Description

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

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Product details

Paperback: 448 pages

Publisher: O'Reilly Media; Second edition (October 20, 2013)

Language: English

ISBN-10: 1449367615

ISBN-13: 978-1449367619

Product Dimensions:

7 x 1 x 9.2 inches

Shipping Weight: 2 pounds (View shipping rates and policies)

Average Customer Review:

4.2 out of 5 stars

68 customer reviews

Amazon Best Sellers Rank:

#444,996 in Books (See Top 100 in Books)

Time-consuming, fruitless hunting for resources mentioned in the book. All the bit.ly links mentioned in the book are broken. They all lead to Russell's page at GitHub. The problem is there are no clear-cut instructions directing the reader to various resources. I needed to find the open-source Python tool. He never mentions exactly what is needed: a full-blown IDE or a text editor. Just a broken link to leave you guessing. Could not find it. Earlier reviews from 2013 show the links to be intact, but they are no longer intact. What once must have been a specific link to a specific resource is now a massive redirect to Russell's main page where you chase your tail in endless loops trying to find your needed resources. Horrible support.

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.Only three additional comments:1) I'm a NON-TECHIE (healthcare) and this book provides such clear guidance that I feel capable of putting it to use, with NO prior experience with, or knowledge of programming. The value of that is not that I'll start programming, however, I can think for myself when it comes to potential uses, limitations, possibilities, challenges for how I want to put this to use.2) You should get the E-BOOK VERSION, not the paper copy as I did, as it'll automatically be up to date, which is crucial as this is an interactive book.3) This book should be required reading for everyone. Why? We need informed customers when it comes to digital products, especially as related to the social web, to understand what it is that you are sharing - blindly for most of us. You're essentially allowing people into your house to go through your drawers and documents. There are situations were you might want that. However, be aware of the kind of access your authorizing and to whom.Matthew A. Russell - wow, well done!

This is more than a "book" - it is a course, and a very well thought through, well supported course at that.The intro alone is more than worth the cost of admission - the easy installation of a VM saved me hours of dev ops headache I would have had to endure in my Python explorations. And it just gets better from there - everything is set up for the reader's convenience - just hit Ctrl-Enter and you're revealing the secrets of LinkedIn or Twitter or whatever.The author clearly poured a lot of effort into his project, and it shows: this book sets a new standard for technical books (at least any technical books I've seen). If you have the slightest interest in the topic, check it out.

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.Mining the Social Web is exceptionally well written covering all major social media platforms. Mr. Russell is also very approachable and answers questions very quickly.I really can't say enough good things about this book and how it sets the bar high for future technical books!

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.I also had the pleasure of interviewing Matthew Russell about this book on The Data Skeptic Podcast where we had the chance to have an interesting discussion about the book.

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.An addendum - SUPER fast support.

Overall a good resource. Gave me enough of a background that I could get a Twitter reader up and running, which I could then modify to do the specific task that I needed to do. A bit complex to set up the operating environment that the author recommends, but instructions were clear and I was able to get it to work without too much angst.

It was an okay book, but seemed to jump around and ramble quite a bit.

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