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Mining the Social Web by Matthew A. Russell

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Closing Remarks

This chapter got you up and running, and illustrated how easy it is to use Python’s interactive interpreter to explore and visualize Twitter data. Before you move on to other chapters, it’s important that you feel comfortable with your Python development environment, and it’s highly recommended that you spend some time with the Twitter APIs and Graphviz. If you feel like going out on a tangent, you might want to check out canviz, a project that aims to draw Graphviz graphs on a web browser <canvas> element. You might also want to investigate IPython, a “better” Python interpreter that offers tab completion, history tracking, and more. Most of the work we’ll do in this book from here on out will involve runnable scripts, but it’s important that you’re as productive as possible when trying out new ideas, debugging, etc.

An interactive Protovis graph with a force-directed layout that visualizes retweet relationships for a “JustinBieber” query

Figure 1-4. An interactive Protovis graph with a force-directed layout that visualizes retweet relationships for a “JustinBieber” query

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