Inspired by this question, I'm wondering whether any work has been done on topic models for large collections of extremely short texts. My intuition is that Twitter should be a natural inspiration for such models. However, from some limited experimentation, it looks like standard topic models (LDA, etc) perform quite poorly on this kind of data.
Does anyone out there know of any work which has been done in this area? This paper talks about applying LDA to Twitter, but I'm really interested in whether there are other algorithms which perform better in the short-document context.