I'm working on a site with a "digg-reddit-dzone-like" feature. How should I select the front page stories? Are there any standard references for this type of algorithms? Best practices? Caveats? Any Hacker suggestions?
Can I recommend the book "Programming Collective Inteligence" (http://www.amazon.com/Programming-Collective-Intelligence-Bu...)? It doesn't actually describe a Reddit-like algorithm but it does describe looks of recommendation algorithms along with practical Python code. Should get you thinking in the right direction.
the algorithms in this book might get you thinking in generally the right direction, but you might miss out on a couple of critical ingredients -- namely, time-based decay functions that make things float and sink (and float again -- dont forget that!), weighting things based on a user's "input worth" (how much you value someone's vote), and so on.
i see these three components as being the basic broth for a good "organic ranking" site:
1. time since the article was submitted, probably represented logarithmically.
2. how many votes came in, measured by how quickly they came in from the articles submission and how far apart each vote is.
3. the "weight" of the users voting on the article.
I would say just do something which takes into account how quickly items are getting voted on and how many comments vs. votes it has. Also take into account sometimes there will be more people on site than others; If you get a swarm of people around the same time (i.e. launch), some items submitted around that time will get tons more votes than things submitted an hour ago - those stories may not have been exactly "less popular", just had less users to make the votes count.
