Over time the readership and topics covered of HN has grown and maybe the quality has gone down. Perhaps one way of solving this problem is to find a way to present a smaller subset of data to different groups so that they can focus on the areas they like?
My favourite kind of posts are big data, web app architecture and functional programming. If my view of HN was skewed by my interests, then my perception of the quality of HN would improve. Chances are that other people would fit into my interest groups and hopefully that would promote tighter, smaller groups and perhaps the quality would increase.
Stackoverflow's tag system seems to work well, but assigning tags would introduce extra burden on people (and another area for disagreement). I like the idea of a machine learning approach where I see articles based on the content on previous articles I enjoyed (via voting). The same could work for comments. Going further, perhaps this could even suggest people with similar interests to yours.
That would deprive you of what I see as one of the greatest benefits of HN - exposure to ideas outside, but related to, your specific area of interest. I've found many interesting items that I would never have sought or subscribed to.
This sounds like Reddit's approach of creating sub-reddit's for different topics (e.g. proggit). This works very well in terms of filtering content.
It doesn't solve the quality of discussion issue, but it does filter the audience which offers some improvement. The quality of discussion varies highly on Reddit -- popular posts are inundated with juvenile comments, while highly focused posts occasionally have decent discussion.
You could apply the same techniques to comments. Voting up comments I enjoy reading would promote comments I like (and hopefully drown out the ones I don't). Whether this would look at the contents of the comments or just increase the weight of the commentator is up for discussion.
A possible counterpoint to this is that in some big cities you do have forms of anonymous camaraderie. I live in the largest city in south america (são paulo), and once I moved here my biggest surprise was how intimate this place could be in comparison with the much smaller places I had lived in before. While in the subway other people are complete strangers and won't receive a cursory greeting, if you do ask someone for help or information it's highly likely that you will get a very polite answer in return, no matter how weird, agressive, poor, or shabby looking you are (I've seen from bums to well-dressed business-people being treated the same way when asking for information in the subway). Also any reasonably self-contained place in this city creates familiarity--I know my butcher by name, the people from the fruit and vegetable market (there are a few in every neighborhood) know me and my wife, I talk to the owners of the nightclubs and restaurants I go to, it is perfectly acceptable to talk to strangers when lining up for the movies (but not necessarily inside the movies, although I've seen people making friendships in this way), etc. The secret seems to be that to create intimacy and trust you need to build some form of a smaller spaces where people can be identified and recognized inside the "big city". Continuing with the city analogy, as long as there are spaces where you will face consequences for misbehaving, social trust is built.
This suggests that a way to improve HN is to add more explicit punishments for bad behavior, preferably moderated.
I find the comment scores useful at a glance to note contributions the community likes. I haven't been here that long, but what is the HN obsession with discussion/comments anyways? Good links are good links. That is the first draw to HN isn't it? Current/fresh relevant links/news items
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[ 3.5 ms ] story [ 33.5 ms ] threadMy favourite kind of posts are big data, web app architecture and functional programming. If my view of HN was skewed by my interests, then my perception of the quality of HN would improve. Chances are that other people would fit into my interest groups and hopefully that would promote tighter, smaller groups and perhaps the quality would increase.
Stackoverflow's tag system seems to work well, but assigning tags would introduce extra burden on people (and another area for disagreement). I like the idea of a machine learning approach where I see articles based on the content on previous articles I enjoyed (via voting). The same could work for comments. Going further, perhaps this could even suggest people with similar interests to yours.
It doesn't solve the quality of discussion issue, but it does filter the audience which offers some improvement. The quality of discussion varies highly on Reddit -- popular posts are inundated with juvenile comments, while highly focused posts occasionally have decent discussion.
A visible score would indicate what sort of comments are valued by the community, and the extent to which they are valued.
This suggests that a way to improve HN is to add more explicit punishments for bad behavior, preferably moderated.