Comment by bdunn
14 years ago
Considering it's probably tricky to programmatically determine what a nasty comment is, I'm assuming you'll figure out whether a comment is good/bad based on the ratio of upvotes to downvotes, and penalize those who voted against the grain.
I get this, but wouldn't this lead to making HN more conformist than it sometimes already is? "Either you agree with the majority of us about X, or..."
it's probably tricky to programmatically determine what a nasty comment is
I've actually been working on that problem with a bot that assists in moderating a subreddit using a text classifier. It's tricky, and needs more work, but it is not impossible.
it's not that hard. Those that work with classifiers, this kind of thing is pretty easy. Identifying sarcasm and irony are hard, but 'nasty comments' can be identified pretty simply using the well known text classifier algorithms. You find the training data and use it to train something like an SVM.
I'd be surprised if pg hasn't experimented with it at least a bit given his history with text classification algorithms.
Out of curiosity, what subreddit is it?
/r/ronpaul
As you might expect, a subreddit about a politician with (in)famously devoted followers attracts its share of strife. It can be difficult to distinguish legitimate arguments from flamebait, and there's no shortage of people eager to take any bait offered. I should note that I'm not actively running the moderation bot at the moment.
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I'm sure that the author of "A plan for spam" (introducing the idea of bayesian filtering to recognize spam) can find a way to classify nasty comments.