However, that loop is indirect and has no guarantees of being closed. And moreover it is not transparent, which means that it is very difficult for the user to see that it is happening.

There is a possibility that +1 will still work as envisioned; however that will require an awareness of the social aspect that you mention. Do you perhaps have a proposal as to how this awareness could be increased?

Beyond linguistic nitpicking, I think that the reward to the user does not need to come directly from their own feedback (as it would when using relevance feedback to improve the current search). In the case of Facebook, the reward is social, and rather indirect. Sharing an item does not directly let you find more items of interest, instead you are giving something to your friends (who will hopefully be grateful rather than annoyed). In turn, you will be given shared items by your friends, but it is not a direct exchange. While in some cases there is a more direct loop in the form of comments, I don’t think that’s the predominant case.

For +1 to succeed there are different ways. One is using the feedback directly to profile the user and improve search results (an advantage for Google over other such systems). The other is making users understand that they are helping their friends, and that they benefit from their friends’ suggestions, emphasizing the social aspect of it.

(And note that at the end of the day, you didn’t actually +1 this second cafe. You only found it via your own +1 on the first cafe. So you can keep the secret to yourself a little bit longer if you want.)

This is the second use case, the thing that +1 doesn’t actually do, that I wish it did. And it’s called “relevance feedback”.

But yes, you are absolutely correct. The point of +1 is to help my friends find things that I have already found. But what +1 does not do is help me find things that I have not yet found, to go deeper into a set of results by reshuffling around the results of my search, so as to more closely match the information found in the thing that I have +1′ed. The whole point of my post was to clearly distinguish these two use cases.

If you have a precision-oriented need, then you don’t need explicit relevance feedback. You are more than likely fine with a system that trains itself on both the explicit and implicit actions of other users (either worldwide or even just your friends — still is training data) so as to make your search for [coffee shop chicago] a little better.

Unless I misunderstand what the explicit actions of others users/friends are, isn’t this just the point of +1? Producing a clearer signal for ranking searches like this? I would imagine the explicit recommendations of my friends for [coffee shop seattle], for instance, is much better than click-through at finding me a coffee shop I would actually like, given that my friends and I are hipster café snobs. I would think that, when my friends google [coffee shop seattle], they are browsing more than anything, sullying click-through’s signal-to-noise wrt my results.

Perhaps this is something you had in mind.