SwearTweet: a Live API Twitter Graph

This is a graph that I created using Processing in order to determine what the most popular swear word on Twitter is. After completing the original design, I found that the dirty words I was using (the 7 Dirty Words by George Carlin) did not create an entertaining graphing experience. There were only two words that grew at any measurable rate, so I decided to take those words and race then against the # and @ symbols, thus providing the viewer with an understanding of just how often these swear words appear online.

There were two counters, one that tracked each individual usage of the words and symbols, and one that took the total number and continued to add onto it after the bar reset to the bottom of the screen.  This allowed the user to see just how close these words were in terms of usage, as the numbers were always shockingly close.

The bars that are in this piece where simply designed in Photoshop, and were added in to make the piece more visual pleasing. The images have been removed from the attached code in the following step.

This project was created for David Bouchard's (Author of the Keystone Processing Library) MPM 505 Class final project, which was presented in December 2012.

I have included the code in order to allow other users to experiment with this.
I have removoed my personal Twitter information, which will have to be replaced with information from the a user in order to work. I have also highlighted the section that allows you to determien which words to search for in the twitter stream, allowing users to enter in whatever words they wish to be used in the program.

I have also replaced the images Used for the bars with rectangles, to allow for a more diverse usage.
The code is located within the following step.

Here is the code, with the personal Twitter information removed. Just replace is with your own info that you can get from the Twitter developer page.

You can also replace the search terms with any words or symbols that you would like. The example of the tweets shows just how vulgar the site can be, so be warned that the language is fairly inappropriate!