Since the earliest days of the "semantic web,", millions of dollars and hours of coding effort have been thrown at the problem of really organizing large corpuses of information, with two approaches emerging: rigid ontologies (like the Dewey Decimal system) that require a system's users to be deeply expert in the structures they're working in; and "folksonomies" (aka hashtags), which allow anyone to tag anything with anything, and leads to fragmentation (like #sign or #signs; or #photos, #pix, and #pictures, etc).
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Maciej Ceglowski's "The Social Graph is Neither" is a scathing, spot-on critique of the deceptive and seductive simplicity of "social graphs" which purport to represent human interaction and relations through mathematical modelling. As with many "semantic web" projects, social networks can only achieve any kind of usable scale and coherence by simplifying the relationships they model to the point of triviality.
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One big sticking point is privacy. Do I really want to find out that my pastor and I share the same dominatrix? If not, then who is going to be in charge of maintaining all the access control lists for every node and edge so that some information is not shared? You can either have a decentralized, communally owned social graph (like Fitzpatrick envisioned) or good privacy controls, but not the two together.
There's another fundamental problem in that a graph is a static thing, with no concept of time. Real life relationships are a shared history, but in the social graph they're just a single connection. My friend from ten years ago has the same relationship to me as the friend I dined with yesterday. You're left with forcing people (or their software) to maintain lists like 'Recent Contacts' because there is no place in the model to fit this information.
"No problem," says Poindexter. "We'll add a time series of state transitions and exponentially decaying edge weights, model group dynamics as directional flows, and pass a context object in with each query..." and around we go.
pThis obsession with modeling has led us into a social version of the Uncanny Valley, that weird phenomenon from computer graphics where the more faithfully you try to represent something human, the creepier it becomes.