Unless you’ve been cryogenically frozen for the past couple of years, you’ve no doubt heard of Twitter—a microblogging service that can be used to broadcast short (maximum 140 characters) status updates. Whether you love it, hate it, or are indifferent, it’s undeniable that Twitter has reshaped the way people communicate on the Web. This chapter makes a modest attempt to introduce some rudimentary analytic functions that you can implement by taking advantage of the Twitter APIs to answer a number of interesting questions, such as:

This chapter analyzes relationships among Twitterers, while the next chapter hones in on the actual content of tweets. The code we’ll develop for this chapter is relatively robust in that it takes into consideration common issues such as the infamous Twitter rate limits,^[23] network I/O errors, potentially managing large volumes of data, etc. The final result is a fairly powerful command-line utility that you should be able to adapt easily for your own custom uses (http://github.com/ptwobrussell/Mining-the-Social-Web/blob/master/python_code/TwitterSocialGraphUtility.py).