(nods) I’ve contemplated in other contexts a fully collaboratively-filtered forum… that is, one in which the sort-order for threads to read is controlled by their popularity (karma) weighted by a similarity factor—where an upvote given by someone whose prior voting patterns perfectly match yours is worth 10 points, say, and given by someone whose priors perfectly anti-match yours is worth −10 points, and prorated accordingly for less-perfect matches.
But mostly, I think that’s a very useful way to allow large numbers of users with heterogenous values and preferences to use the same system without getting in each others’ way. It would make sense for a popular politics discussion site, for example.
(The simple version just creates a series of echo chambers, of course. Though some people seem to like that. But further refinements can ameliorate that if desired.)
LW doesn’t seem to have that goal at all. Instead, it endorses particular values and preferences and rejects others, and when discussions of filtering come up they are framed as how to more efficiently implement those particular rejections and endorsements.
So mostly, collaborative filtering seems like it solves a problem this site hasn’t got.
You can use collaborative learning for other purposes. For example, suppose I wanted to show a user posts which Eliezer Yudkowsky would upvote (a “Things EY would Upvote” tab...), rather than posts they personally would upvote. This allows a moderator to implicitly choose which component of users has the “right” taste, without having to explicitly upvote/downvote every individual post.
I don’t know if imposing one individual’s taste is such a good idea, but it is an option. It seems like you should think for a while about what exactly you want, rather than just proposing mechanisms and then evaluating whether you like them or not. Once you know what you want, then we have the theoretical machinery to build a mechanism which implements your goal well (or, we can sit down for a while and develop it).
Also, it is worth pointing out that you can do much better than just weighting votes by similarity factors. In general, it may be the case that Alice and Bob have never voted on the same comment, and yet Alice still learns interesting information from Bob’s vote. (And there are situations where weighting by similarity breaks down quite explicitly.) My point is that instead of doing something ad-hoc, you can employ a predictor which is actually approximately optimal.
It seems like you should think for a while about what exactly you want, rather than just proposing mechanisms and then evaluating whether you like them or not.
Fair enough. Apologies for wasting your time with undirected musings.
In terms of what I want, everything I can think of shares the property of being more useful in a more heterogenous environment. I put together a wishlist along these lines some months ago.But within an environment as homogenous as LW, none of that seems worth the effort.
That said, I would find it at least idly interesting to be able to switch among filters (e.g., “Things EY would upvote”, “Things Yvain would upvote”, etc.), especially composite filters (e.g., “Things EY would upvote that aren’t things Yvain would upvote,” “90% things EY would upvote and 10% things he wouldn’t”, etc.).
(nods) I’ve contemplated in other contexts a fully collaboratively-filtered forum… that is, one in which the sort-order for threads to read is controlled by their popularity (karma) weighted by a similarity factor—where an upvote given by someone whose prior voting patterns perfectly match yours is worth 10 points, say, and given by someone whose priors perfectly anti-match yours is worth −10 points, and prorated accordingly for less-perfect matches.
But mostly, I think that’s a very useful way to allow large numbers of users with heterogenous values and preferences to use the same system without getting in each others’ way. It would make sense for a popular politics discussion site, for example.
(The simple version just creates a series of echo chambers, of course. Though some people seem to like that. But further refinements can ameliorate that if desired.)
LW doesn’t seem to have that goal at all. Instead, it endorses particular values and preferences and rejects others, and when discussions of filtering come up they are framed as how to more efficiently implement those particular rejections and endorsements.
So mostly, collaborative filtering seems like it solves a problem this site hasn’t got.
You can use collaborative learning for other purposes. For example, suppose I wanted to show a user posts which Eliezer Yudkowsky would upvote (a “Things EY would Upvote” tab...), rather than posts they personally would upvote. This allows a moderator to implicitly choose which component of users has the “right” taste, without having to explicitly upvote/downvote every individual post.
I don’t know if imposing one individual’s taste is such a good idea, but it is an option. It seems like you should think for a while about what exactly you want, rather than just proposing mechanisms and then evaluating whether you like them or not. Once you know what you want, then we have the theoretical machinery to build a mechanism which implements your goal well (or, we can sit down for a while and develop it).
Also, it is worth pointing out that you can do much better than just weighting votes by similarity factors. In general, it may be the case that Alice and Bob have never voted on the same comment, and yet Alice still learns interesting information from Bob’s vote. (And there are situations where weighting by similarity breaks down quite explicitly.) My point is that instead of doing something ad-hoc, you can employ a predictor which is actually approximately optimal.
Fair enough. Apologies for wasting your time with undirected musings.
In terms of what I want, everything I can think of shares the property of being more useful in a more heterogenous environment. I put together a wishlist along these lines some months ago.But within an environment as homogenous as LW, none of that seems worth the effort.
That said, I would find it at least idly interesting to be able to switch among filters (e.g., “Things EY would upvote”, “Things Yvain would upvote”, etc.), especially composite filters (e.g., “Things EY would upvote that aren’t things Yvain would upvote,” “90% things EY would upvote and 10% things he wouldn’t”, etc.).