Looking closely at the main screenshot, I only see one tweet related to product support. Look forward to future posts discussing their filtering methods. Raw word list? Bayesian learning? 440+ tweets is not insignificant, but experience tells me this takes about 3 or 4 hours per day just to manually identify/categorize using a sane level of effort.
The next two parts will have more detail, but the short answer is "yes" to both a raw word list and a Bayesian filter in terms of techniques we've tried here. One of the simplifying things that makes the problem a little easier is that we don't try to classify beyond "does this need an immediate reply or not."
