Have you ever wanted to use the APIs of the main Social Media platforms, to download and analyse data, manipulate it and combine it with other data sources?

Then this excellent, updated book is for you.
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The sample code, written in Python, is not just available to download, but is also provided via Github. Better even than that, the author, Matthew Russell,

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 is as simple as installing Virtual Box, installing Vagrant, cloning the 2nd edition’s Github archive, and typing “vagrant up.”  You can execute the examples for yourself in the virtual machine; modify them; and use the virtual machine for your own projects, since it’s a fully functional Linux system with Python, Java, MongoDB, and other necessities pre-installed.

In setting up the virtual machine on my Linux laptop I encountered a problem when I allowed the PC to go to sleep. I raised an issue on Github, as the author prefers, and I had a response with a suggested resolution back from the author within minutes!  That’s a great service.

I’m still working through the first chapter on Mining Twitter which, at 38 pages, has loads of useful code examples. All of these can be run live in the IPython server and the code experimented with to your heart’s content.

And of course, since all the code is hosted on Github, you can keep up to date with any changes by pulling down an update version.

Despite my limited time to play with the code so far, this book, and its exemplary code base, is unhesitatingly recommended.

To quote from an Amazon review:

I really can’t say enough good things about this book and how it sets the bar high for future technical books!

First look: Mining The Social Web – Data Mining Facebook, Twitter, Google+ etc
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