21 Recipes for Mining Twitter: Distilling Rich Information from Messy Data - PDF
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This intentionally terse recipe collection provides you with 21 easily adaptable Twitter mining recipes and is a spin-off of Mining the Social Web (O'Reilly), a more comprehensive work that covers a much larger cross-section of the social web and related analysis. Think of this ebook as the jetpack that you can strap onto that great Twitter mining idea you've been noodling on—whether it’s as simple as running some disposible scripts to crunch some numbers, or as extensive as creating a full-blown interactive web application.
All of the recipes in this book are written in Python, and if you are reasonably confident with any other programming language, you’ll be able to quickly get up to speed and become productive with virtually no trouble at all. Beyond the Python language itself, you’ll also want to be familiar with easy_install (http://pypi.python.org/pypi/setuptools) so that you can get third-party packages that we'll be using along the way. A great warmup for this ebook is Chapter 1 (Hacking on Twitter Data) from Mining the Social Web. It walks you through tools like easy_install and discusses specific environment issues that might be helpful—and the best news is that you can download a full resolution copy, absolutely free!
One other thing you should consider doing up front, if you haven’t already, is quickly skimming through the official Twitter API documentation and related development documents linked on that page. Twitter has a very easy-to-use API with a lot of degrees of freedom, and twitter (http://github.com/sixohsix/twitter), a third-party package we’ll use extensively, is a beautiful wrapper around the API. Once you know a little bit about the API, it’ll quickly become obvious how to interact with it using twitter.
Finally—enjoy! And be sure to follow @SocialWebMining on Twitter or “like” the Mining the Social Web Facebook page to stay up to date with the latest updates, news, additional content, and more.