I did something similar to this with tweets during the Boston Marathon bombing [0]. One of the coolest things that I saw was that the topics themselves were nea

I did something similar to this with tweets during the Boston Marathon bombing [0]. One of the coolest things that I saw was that the topics themselves were neatly ordered in time. In other words, you can visualize how the distribution of vocabulary evolves with time [1]. It would be interesting to extend the LDA model to include a temporal variable. Never got around to doing it, but it seems like it would work well for social media data. [0] http://blog.dc.esri.com/2013/04/18/the-evolution-of-discussion-around-the-boston-marathon-events/ http://blog.dc.esri.com/2013/04/18/the-evolution-of-discussi... [1] http://blog.dc.esri.com/files/2013/04/topic-distribution2.png http://blog.dc.esri.com/files/2013/04/topic-distribution2.pn...