FWIW HN shows the signs of this deterioration in the sense of a certain respect. I like to model forums by the percentage of their posts which lead to information gain. Ideally, I'd like to formulate this as some sort of K-L divergence with some sort of temporal decay on a binary variable. In a rough handwavey sense, I find that the information gain from many HN posts is high but HN comments is low, but it would be interesting to me if we could think up something more concrete.
The worst examples are posts on Google, Facebook, or Apple. Most commenters could be replaced by /r/subredditsimulatorGPT. On the other hand, it might be that I have just fully mined HN as an information source. It's likely this is true, in which case I should find some mechanism to reduce the content here.
One idea I have had is the idea of overlay networks - essentially the underlying data of the forum is the same, but we place intentionally different filtering mechanisms on the view layer. One could be "high karma users". Another could be "actively followed users". Anyway, just thoughts.