Crowding out the Social Graph

A graph tells you how the dots are connected. When the dots are people and the connections are relationships, geeks like to call this the Social Graph. If you sit on it, you can get a picture, an aerial snapshot of who knows who.

Math and computer science dudes love graphs. It’s fun to see how closely people are connected by counting the steps between them. The idea that such a picture can give you a global perspective on something as subtle and complex as social relations is deeply appealing. However, I think it’s a model that misses something from real social structures.

Take a look at a my Facebook graph from a while back, visualised using the TouchGraph tool:

My Graph

A really nice feature of this tool is that it uses the graph connectivity to colour recognisable clusters of people. I can put a name to several of them. The red ones are the circus dudes, the adjacent blue ones are old school circus. The limes are from computer science.

These real-life clusters — let’s call them ‘crowds’ — have been cleverly inferred by the algorithm but they could have easily been defined by me (or any other member of the crowd). This would have the advantage that instead of each of us friending each other we only have to join the crowd.

As well as being a lot less work all round, this also reflects the fact that, for quite a few bods, our relationship is based solely on our mutual crowd membership. If you drift away from a crowd in the future then you naturally lose those connections. Easy come, easy go.

Having a crowd explicitly defined would also make it easy to target announcements, photos, etc.

I don’t think Facebook Groups or Networks cover it in practice. Groups are mostly used by strangers to express affinities rather than have any consequence. The Networks are perhaps closer to crowds but they are generally so large they become meaningless (Birmingham UK has over 21k members!). How often do you meet someone via a Facebook Group or Network?

In real life, friendships emerge within the context of a shared crowd, whether it’s based on work, shared interest, experience or location. Online social networks in which undifferentiated ‘friend’ relations spark into existence more as a courtesy than anything meaningful still seem fundamentally odd.

Thanks to Jon for badgering this post out of me.

One thought on “Crowding out the Social Graph

  1. Thanks for writing this up finally, “circles and crowds” make a lot more sense to me now. I hadn’t quite twigged that you were proposing it as a complete replacement of this whole “friend” thing you have on Facebook etc., and what the implications of that are. I’m much more of a believer now. 🙂

    I definitely think you should put more effort into trying to explain the dynamics of Bodder – I know they will emerge from usage and the only way to deeply understand them is to use them, but there will be plenty of times that you need to explain why it’s great without making them use it for ages (e.g. new users, investors, etc.). You might tell them only part of the story – just enough to make them sign up – but it’d be useful to have it in writing (and diagrams) anyway.

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