I'm only half joking. Fundamentally, the thread is about a filtering system.
I have done some research on this (unpublished), and I got a really good performance on predicting hacker news votes by just counting how many new words (not stopwords, not very-high-frequency words) a comment was adding to a thread. Just using a few variations on this theme predicted better than word counts or bigram features.
Fundamentally, though, I disagree with machine learning- based approaches as they can only _reinforce_ present behavior, and we'd like to shape voting behavior.
(also what if the ML only provided feedback while one is typing the comment?)