There seems to be a problem primarily on reddit. It’s antecdotal but, it seems good content gets buried. Pick a popular subreddit (say r/videos), and select “Top” posts for “All Time”. You will notice that a lot of that continent is newer and it appears that the quality is not the same. About a year ago, you could perform the same action and get the “oldie by goodie” type content. I think the methods we use to gauge content quality doesn’t scale when a site is overloaded with users. I haven’t yet seen it happen on HN, maybe because the quality of users is “better”.
I think that's sort of like asking why the list of highest grossing movies is so biased toward recent ones rather than all time classics. In both cases inflation is ignored. to get a "best of all time" ranking on HN/Reddit, I think you'd have to normalize by the number of active users on the date of the post.
Inflation of both the price of a movie, and of the movie-watching population. The proper ranking would be the inflation-adjusted number of movie dollars spent per capita on a given movie.
It might be simpler to look at the share of the population that went to see the movie. That should tell us how influential a movie was compared to another.
Not sure how active users work, but I wonder if that would account for posts that make it to r/all. If a user scrolls past a post, hides a post, reports, clicks on a post, etc., then that should count as an impression. The inflation-adjusted metric would then be upvotes/impressions.
Even accounting for inflation, there are tons of other factors that can affect it.
If movies in general were more popular in some years than others, or if there were new features at some points that cost a premium, it skews the numbers.
Yeah something like the percentage of total active users who upvoted it may make more sense for subreddits that experience large growth in number of users.
I often find myself wishing you could do top posts by year for each year because those posts for previous years can be nearly impossible to find without going back pages and pages of the top of all time
Interestingly I tend to find that if the comment count is higher than the score it often means the article is somehow wrong and everyone has jumped in to say so. Though I guess that depends a little on the score count too.
Would be interesting to do a meta analysis to see how much valuable information there is in the different categories of score comment ratios!
Cool idea. I really enjoy playing with variants of hacker news, like this, and e.g tagger news.
I wonder if a diverging color scheme might make the ratios easier to read, at a glance. E.g. a red scale for ratios > 1, and a blue scale for ratios < 1.
I would love to see a system for flagging or downranking posts and/or threads that are beating a dead horse - by somehow recognizing similarity with a critical mass of past posts.
If movies in general were more popular in some years than others, or if there were new features at some points that cost a premium, it skews the numbers.
E.g X standard deviations above the average = score.
I often find myself wishing you could do top posts by year for each year because those posts for previous years can be nearly impossible to find without going back pages and pages of the top of all time
Would be interesting to do a meta analysis to see how much valuable information there is in the different categories of score comment ratios!
I wonder if a diverging color scheme might make the ratios easier to read, at a glance. E.g. a red scale for ratios > 1, and a blue scale for ratios < 1.