[noelwelsh]

This is interesting stuff, but I wonder has anyone verified the results in practice? These methods are all quite simple. They assume, for example, that the quality of an item is independent of the quality of the surrounding content. This is clearly not true. When Steve Jobs died, for example, no other new in the tech community was going to get air time. There is also the need for a variety of content. I think we all know how boring it is to read endless "I wrote X in Y" posts on HN, where X is some simple software system like a blog and Y is the language du jour (Node.js / Go / whatever).

In the machine learning community the above problems are addressed with submodular loss functions, bandit algorithms, and no doubt other methods I don't know about. Now I don't value complexity for its own sake, so I wonder if the additional power these approaches bring is warranted.