Twitter's social network is endlessly fascinating because of its many different connection channels: there are hashtags, followers, retweets, and replies, all connecting users in different ways. Using the network analysis package NetworkX, we'll take a look at how to make sense of these channels. We'll cover some of the basics of network theory, including types of networks and how measure influence in a network. We’ll use the Twitter API to gather data for our analysis, and then apply the network theory we learn to that data. Students will leave with knowledge of how to think about networks from a network theory perspective and may even find out something interesting about their own Twitter network. Students should have an intermediate knowledge of Python, including the ability to write functions and understand iterables. Knowing how to use IPython Notebook will also be helpful, since the materials will be in that format. Having both NetworkX and IPython notebook, as well as matplotlib, which we’ll use for visualization, installed prior to the tutorial is necessary, as we’ll only spend a few minutes covering installation. These packages can be pip installed, or can be installed through a distribution like Anaconda or Enthought Canopy.