One way to promote quality is to crack down on low-quality content (which is something that HN does and you've done a good job at doing. :P).
For example, many popular subreddits support the making of image macros/memes. Many of the serious subreddits have a) banned the use of image macros/memes and/or b) forced the sub to use text posts only, which forces the submitter to add discussion, and also reduces the incentive for karma-gaining since text posts generate no karma.
Another approach is to promote original content [OC], which gives an incentive to submitters to submit unique content instead of just being the first to post a submission to a new article on TechCrunch for internet points. The subreddit /r/dataisbeautiful has done this very well. (I really wish Reddit would remove its 10:1 rule, which was made to punish self-promoters and is a different issue entirely)
And of course, the standard machine learning techniques can be used to predict the probability of a post being good given, for example, a) keywords in title b) quality of domain's previous submissions c) quality of user's previous submissions, etc.
For example, many popular subreddits support the making of image macros/memes. Many of the serious subreddits have a) banned the use of image macros/memes and/or b) forced the sub to use text posts only, which forces the submitter to add discussion, and also reduces the incentive for karma-gaining since text posts generate no karma.
Another approach is to promote original content [OC], which gives an incentive to submitters to submit unique content instead of just being the first to post a submission to a new article on TechCrunch for internet points. The subreddit /r/dataisbeautiful has done this very well. (I really wish Reddit would remove its 10:1 rule, which was made to punish self-promoters and is a different issue entirely)
And of course, the standard machine learning techniques can be used to predict the probability of a post being good given, for example, a) keywords in title b) quality of domain's previous submissions c) quality of user's previous submissions, etc.