I agree, there are issues with NB such as the ones you brought up. I don't think document length is the real offender here though. This really boils down to noise and how well you filter and devalue it. Stacking more filters like stemming, stopwords, and high frequency features definitely helps in this case to the point where longer documents can actually improve accuracy. Additionally, tuning your ngram lengths or using variable lengths, choosing between word or character ngrams, and limiting your distribution size all will help depending on what you're trying to categorize.