3 ms·
I reverse-engineered the HN ranking algorithm a few years ago [1]. To answer your question, posts have a sudden drop due to several types of penalties. Many pos
by kens 3y ago
I reverse-engineered the HN ranking algorithm a few years ago [1]. To answer your question, posts have a sudden drop due to several types of penalties. Many posts are penalized from the start due to their title or domain. A "controversy" penalty kicks in if an article has more comments than upvotes and at least 40 comments; this penalty is usually the reason why an article catastrophically drops. Other penalties are applied by the moderators. If the voting looks suspicious, a "voting ring" penalty is applied. I found that penalties were very common: 20% of front page articles were penalized and 38% of second page articles. There have been changes to the ranking algorithm since I looked at it, but it is generally the same.
[1] https://www.righto.com/2013/11/how-hacker-news-ranking-really-works.html https://www.righto.com/2013/11/how-hacker-news-ranking-reall...
- redbell 3y ago+1, and thanks for taking the time to work on this! I've always wondered how HN ranking works until this moment where every question I had regarding this is being answered in the article. Also, the article is more than a decade ago, and I'm wondering if there have been any considerable updates to the HN ranking algorithm since then?
- cbeach 3y agoI've also tried reverse engineering the algorithm recently to plot a scattergraph of story ranks vs age-adjusted score. I'm looking for outliers in order to work out where HN moderators have intervened. https://docs.google.com/spreadsheets/d/1q6HS4Gcw8KVp5nTRC_H0T6Fg5jiGbo6YgWwrOq5WXdo/edit?usp=sharing https://docs.google.com/spreadsheets/d/1q6HS4Gcw8KVp5nTRC_H0... It turned out to be very difficult as there are so many arbitrary factors, and the HN API doesn't expose those factors. It's good to see the OP's graphs over time, showing the large jumps which clearly indicate manual intervention. That's a much more effective approach than my own analysis. My motivation is to surface any patterns in those interventions. Annecdotally I notice that positive news about Elon Musk and his companies has been suppressed more than once. * Elon Musk nobel prize nomination: https://twitter.com/chrisbeach/status/1760277351621878066 https://twitter.com/chrisbeach/status/1760277351621878066 * xAI open-sourcing Grok: https://twitter.com/chrisbeach/status/1769755409391222868 https://twitter.com/chrisbeach/status/1769755409391222868 Obviously, the moderators are responding to things like user flags, but in my opinion there should be more transparency around this, in order to prevent users brigading certain topics, using flags inappropriately, to manipulate the narrative.