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I’ve written and talked a lot about data finding data and then people finding people. Today, someone asked me what that meant in the context of social networks, etc and we ended up with a pretty good example of that concept.
I have two networks – science and music (the data), and the networks related to both (the people). The two networks do not really overlap. In other words since there is no common data, the people are not finding the people. On the other hand, the science and programming networks have some overlap and those people do find each other. I wonder how generalizable this concept is and if there have been any analyses along those lines. Michael, any ideas?
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2 Comments
Deepak – Not really sure I agree with your diagnosis. I can use myself as an example: why don't I know your musical friends? I've read and enjoyed (and occasionally commented on) your occasional musical posts on FriendFeed. But music isn't why I'm on FriendFeed, and so I never quite manage to cross the gap to start really chatting with your friends who are. It's not that I wouldn't like to – I'm pretty sure I'd enjoy it a lot – nor that I'm unaware, but there's an awful lot of communities I'd like to join but don't quite have the time. By way of contrast, programming is a major interest of mine, which is how I've ended up connected to a lot of developers on FriendFeed.
Deepak – Not really sure I agree with your diagnosis. I can use myself as an example: why don't I know your musical friends? I've read and enjoyed (and occasionally commented on) your occasional musical posts on FriendFeed. But music isn't why I'm on FriendFeed, and so I never quite manage to cross the gap to start really chatting with your friends who are. It's not that I wouldn't like to – I'm pretty sure I'd enjoy it a lot – nor that I'm unaware, but there's an awful lot of communities I'd like to join but don't quite have the time. By way of contrast, programming is a major interest of mine, which is how I've ended up connected to a lot of developers on FriendFeed.