Most of them fail because they don't have enough data, or they're using the wrong kind of data. The main assumption with social recommendations is that I give

Most of them fail because they don't have enough data, or they're using the wrong kind of data. The main assumption with social recommendations is that I give a damn about everything my friends like. With every one of my friends, we have an overlapping interest in at least one category, but but there are about two people in my social network that have an overlapping interest with more than half of my interests. With current engines, they say "Oh, Alice liked the new Katy Perry album, you should check it out", without any understanding that I'm friends with Alice because of she can hold an interesting conversation, rather than a shared music taste. The proper way to do recommendations is to build up a profile of the user, and then match recommendations from people similar to the user. This is exactly what Hunch is doing. I hope they're successful, they're the only ones close to a solution. (Disclaimer, I'm not affiliated with Hunch, but I'm founding a startup using very similar math in a different field).