Visualizing Tons of Tweets

There are more interesting ways to visualize Twitter data than we could possibly cover in this short chapter, but that won’t stop us from working through a couple of exercises with some of the more obvious approaches that provide a good foundation. In particular, we’ll look at loading tweet entities into tag clouds and visualizing “connections” among users with graphs.

Visualizing Tweets with Tricked-Out Tag Clouds

Tag clouds are among the most obvious choices for visualizing the extracted entities from tweets. There are a number of interesting tag cloud widgets that you can find on the Web to do all of the hard work, and they all take the same input—essentially, a frequency distribution like the ones we’ve been computing throughout this chapter. But why visualize data with an ordinary tag cloud when you could use a highly customizable Flash-based rotating tag cloud? There just so happens to be a quite popular open source rotating tag cloud called WP-Cumulus that puts on a nice show. All that’s needed to put it to work is to produce the simple input format that it expects and feed that input format to a template containing the standard HTML boilerplate.

Example 5-17 is a trivial adaptation of Example 5-4 that illustrates a routine emitting a simple JSON structure (a list of [term, URL, frequency] tuples) that can be fed into an HTML template for WP-Cumulus. We’ll pass in empty strings for the URL portion of those tuples, but you could use your imagination ...

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