I wonder what would happen if we run the simple version of that algorithm on LW comments. So that votes would have “polarity”, and so each comment would have two vote-counts, let’s say orange count and blue count. (Of course that would be only optionally enabled.)
Then we could sort the comments by the minimum of these counts, descending.
(I think it makes more sense to train it per post than globally. But then it would be useful only on very popular posts with lots of comments.)
That sounds cool! Though I think I’d be more interested using this to first visualize and understand current LW dynamics rather than immediately try to intervene on it by changing how comments are ranked.
I think a lot of the value that I’d get out of something like that being implemented would be getting an answer to “what is the biggest axis along which LW users vary” according to the algorithm. I am highly unsure about what the axis would even end up being.
Would that even be a meaningful question? Thinking of it as a kind of PCA, there will be some axis, with a lot of correlations, and how you interpret that is up to you.
I’d imagine that once we see the axis it will probably (~70%) have a reasonably clear meaning. Likely not as obvious as the left-right axis on Twitter but probably still interpretable.
I wonder what would happen if we run the simple version of that algorithm on LW comments. So that votes would have “polarity”, and so each comment would have two vote-counts, let’s say orange count and blue count. (Of course that would be only optionally enabled.)
Then we could sort the comments by the minimum of these counts, descending.
(I think it makes more sense to train it per post than globally. But then it would be useful only on very popular posts with lots of comments.)
That sounds cool! Though I think I’d be more interested using this to first visualize and understand current LW dynamics rather than immediately try to intervene on it by changing how comments are ranked.
I think a lot of the value that I’d get out of something like that being implemented would be getting an answer to “what is the biggest axis along which LW users vary” according to the algorithm. I am highly unsure about what the axis would even end up being.
Would that even be a meaningful question? Thinking of it as a kind of PCA, there will be some axis, with a lot of correlations, and how you interpret that is up to you.
I’d imagine that once we see the axis it will probably (~70%) have a reasonably clear meaning. Likely not as obvious as the left-right axis on Twitter but probably still interpretable.