Social Sentiment

Based on the streaming data from twitters “firehose”, and the very cool opengl capabilities of processing I decided to map each tweet out to a 3D globe. Using natural language processing we color the tweets points, and text to a color representing the sentiment of the tweet. Pinkish is negative, Blue is Positive, and white is neutral. Now not all tweets from the stream are created equal. This is because not all users tweet from a geo enabled device. So, in the case that the tweet does not include geographical location data we simply do not plot it on the globe. But every tweet is analyzed by the NL engine and then used in the data set for the radial graph around the globe. Using the great toxi libs I was able to track the tweets floating down the the surface as solids in a voxel grid. They are then converted to a triangular mesh and I draw them out to the screen in the render loop. If you watch them closely you will see the mesh uses the color of the tweet it represents, and mixes colors with nearby tweets creating a colorful mesh of voxely awesomeness. I realize this is nothing more than visual noise. But the intention here was to create something visually entertaining as well (semi-)informative.