That's a nice approach, but a naive bayes classifier doesn't seem like it would be the best method for this particular problem. You probably want to do an N-gr

That's a nice approach, but a naive bayes classifier doesn't seem like it would be the best method for this particular problem. You probably want to do an N-gram analysis, like that performed by libtextcat http://software.wise-guys.nl/libtextcat/ http://software.wise-guys.nl/libtextcat/. This will perform a comparison based on common combinations of letters used (like "wo", "or", "rd"). Seems like it would be more accurate with such a relatively small sample of comments. If you had a list of 10-20 possible candidates, you could narrow it down to just a few.