I've been recently thinking about various graphical ways to represent online communities, those in LJ in particular. There is a bunch of tools that build one sort of graph or another, but none seem to provide a good view of a community the user in question is a part of. While investigating this problem I've built a prototype tool that tries to
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{
return( !(I don't currently plan to distribute) );
}
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You'd also want to make sure that you're counting yourself not only as part of a community centered around these new clusters but that it's the community you're primarily involved in.
I have one friend who is for the most part completely unrelated to the rest of my community. Among my other friends the people fall into two categories where one is twice the size of the other. Oddly enough, the smaller community has ties to the larger that are not just through me thought the friends happen to be geographically and historically distinct.
The whole exercise would be much more accurately (but more complicated) if we could weight the associations between people. For instance: by how often they post on each other's journals.
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If XFN had a more serious following, or lj support, then you could, for example, weight the springs, and then solve the graph as a constraint problem, which would clump the users with the closest relationship. As it is, this isn't possible, and your representation suffers for it: "maruse4ka" (top right) looks far more like an outsider than "lenoyka" (middle left), despite both of them having 2 links. I suppose you could organise your cloud into concentric circles, with the number of links the node has determining what circle they live in: have you investigated that?
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