Both social networking and votable newsfeeds are one-dimensional. Combine the two and you get a kind of Pandora for stories, and for discovering people who like the kind of stories you do.
Mostly I've used my news reader (Google News) just to keep track of blogs and webcomics that I like. Google News also has a thing where friends can recommend stuff, but it's people I already know and it doesn't build on their knowledge.
Facebook, more than anything else, seems like a giant high-school + college reunion. You can cruise around the room and talk to people you already know, and invite new people into the room based only on the fact that they know people you know. This is more functional that what we had before, but only because that was "nothing."
In the end, neither of these technologies is all that interesting because they're one-dimensional and overly simplistic. There's no amplification and focusing going on.
Take newsfeeds like reddit, for example. People vote on stories, which is interesting because we couldn't do it before, with newspapers or television. But anyone can vote on these stories, so the only thing that happens is that a story that might otherwise have gotten buried by the mainstream media will probably surface via a newsfeed. Other than that, however, there's no discrimination about whether that story is interesting to me.
Social networking doesn't do a good job of introducing me to new people that are interested in the same kind of stuff I am, nor does it do any pruning of the existing mob to narrow it down to my interests. When someone wants to be my Facebook friend, I have no clue as to whether this is going to be a beneficial relationship or not.
Now consider Pandora, which uses the "Music Genome Project." This uses crowdsourcing to categorize music, and when I say I like or dislike something, Pandora says "Ah! Now we know a little bit more about you, and can send you other music that people like you seem to like." It's a constant process of refinement and categorization to deliver music that you like better and better.
What's left out of Pandora is the other side (and this is where Pandora might make some real money). Who are the other people who have similar music tastes as you? What if you could, for example, have a party and invite those people? I don't know how this would work out but it sure seems like it could be an interesting experiment.
Now take the Pandora formula and apply it to newsfeeds. As I vote for and against various stories, that information not only raises and lowers the story in the newsfeed, but it also categorizes me. Like Pandora, the newsfeed is constantly categorizing me and grouping me with others like me, so when those others vote up on something, it is suggested to me as well. So instead of wading through what the majority of the unwashed masses are interested in, I have my own group of people like me, finding and filtering stories that I am likely to be interested in. Now when I vote, I'm not just saying I like something, but I get something back, which is the benefit of being in a group like me, and the benefit of their filtering and recommendations.
And again, don't stop there. Now there is a group of people like me. From a social network standpoint, it's very likely that we could have interesting discussions, parties or even dates. And we didn't start out trying to present ourselves in a particular way for a particular agenda; we have been trying to interact honestly with the system because that way we get the best stories; the social networking aspect is a very beneficial side-effect, but not the primary goal of the interaction.
Think about it. Wouldn't you drop your newsfeed and social network in an instant if you had a multidimensional intelligent system like this working for you? I think it will blow the first-iteration systems out of the water (also, it seems like it might be an excellent thing to build on the Google App Engine, since you won't have to worry about scaling when it explodes).
Hi Bruce, thanks for sharing, that are really interesting ideas. Some of them are already implemented in companies Blog: http://blog.coremedia.com. We are using our Recommendation Engine to calculate neighbourhoods between people. Those people which are looking at the same articles like you or which have an equal voting behaviour (thumps up/thumps down) will be in you neighbourhood. Weekly we generate a newsletter which contains a set of links of articles which were rated or read by your calculated fellows. You will also receive a list of the person in your neighborhood. Additionally we have an "explicited" recommondation feature, were you receive a notification if a fellow of yours recommended an article. Would you like to join our blog, visit: https://blog.coremedia.com/cm/login . OpenID and Facebook login is possible.
PS: Thanks for your Book: "Thinking in Java", it helped me a view years ago to learn the language.