I've spent the past week going over the ideas in Chris Dixon's excellent post titled graphs and thought the ideas were powerful enough that they are worth reiterating. The thesis is simple, in recent years many have been focused on social graphs (i.e. graphs bidirectional or one-way “friend” relationships between users) but there are other ways in which users can be connected to each other besides whether they are friends or not. The key points from Chris’s post are excerpted below

Facebook’s social graph is symmetric (if I am friends with you then you are friends with me) but not transitive (I can be friends with you without being friends with your friend).  You could say friendship is probabilistically transitive in the sense that I am more likely to like someone who is a friend’s friend then I am a user chosen at random. This is basis of Facebook’s friend recommendations.

Twitter’s graph is probably best thought of as an interest graph. One of Twitter’s central innovations was to discard symmetry: you can follow someone without them following you. This allowed Twitter to evolve into an extremely useful publishing platform, replacing RSS for many people. The Twitter graph isn’t transitive but one of its most powerful uses is retweeting, which gives the Twitter graph what might be called curated transitivity.
Over the next few years we’ll see the rising importance of other types of graphs. Some

Taste: At Hunch we’ve created what we call the taste graph. We created this implicitly from questions answered by users and other data sources. Our thesis is that for many activities – for example deciding what movie to see or blouse to buy – it’s more useful to have the neighbors on your graph be people with similar tastes versus people who are your friends.

Financial Trust: Social payment startups like Square and Venmo are creating financial graphs – the nodes are people and institutions and the relations are financial trust. These graphs are useful for preventing fraud, streamlining transactions, and lowering the barrier to accepting non-cash payments.

Endorsement: An endorsement graph is one in which people endorse institutions, products, services or other people for a particular skill or activity. LinkedIn created a successful professional graph and a less successful endorsement graph.

Local: Location-based startups like Foursquare let users create social graphs (which might evolve into better social graphs than what Facebook has since users seem to be more selective friending people in local apps). But probably more interesting are the people and venue graphs created by the check-in patterns. These local graphs could be useful for, among other things, recommendations, coupons, and advertising.

One of the things that has been interesting to watch is how many services have tried to build this other sorts of relationship graphs on top of Facebook Connect. Quora has tried to build an endorsement graph from Facebook Connect as a basis while Yelp has tried to build a location graph using Facebook's Instant Personalization and Facebook Connect as the foundation. As more of these sorts of relationships graphs between people and other entities are created it is slowly becoming clear to me that there are many scenarios where Facebook’s graph is not the best starting point.

Take this screenshot of the Facebook Friend’s Activity plugin on Engadget as an example.

What this plugin does is show which of my Facebook friends (i.e. mostly family, coworkers and high school friends) have found interesting on Engadget. I couldn’t help but think back to what Chris Dixon mentioned about Twitter being an “interest graph”. I realized that this feature would actually be more useful if it showed me what Engadget articles people I follow on Twitter found interesting rather than what my Facebook friends did.

As the utility of the social graph grows beyond providing a stream of updates from people in that graph to being reused in other contexts, the lack of universal appeal in some of these relationships will grow more obvious. Using Twitter as an example, I suspect if asked to chose between a widget on TechCrunch that shows what articles are interesting among your Facebook friends versus who you follow on Twitter a non-trivial amount of people would pick the latter.

Similarly I wonder how soon till we start seeing some of the endorsement graphs being built on services like LinkedIn and Quora being leveraged in other places where you need to vet the opinions of strangers such as Amazon or even Monster.com.

There are times I’ve debated with others whether there will be one social graph to rule them all and whether that graph will Facebook’s. Now I ‘m convinced that although their graph is likely to be the largest and most generally applicable in the long term, there is a market for social graphs based on relationship types other than whether someone is a “friend” or not which can still significantly improve the user experience on the Web.

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Monday, August 2, 2010 3:37:39 PM (GMT Daylight Time, UTC+01:00)
I'm sure there will be multiple graphs, but I'm not sure whether Twitter is a better interest graph or just a more fashionable one (I'm assuming 'what Engadget articles people I follow on Twitter found interesting rather than what my Facebook friends did' = Twitter is a better interest graph). There's a segment of the population that values advice from friends over advice from experts - and a reputation graph is going to be really interesting.

The number of graphs that thrive will be limited by our ability to consume and contribute to them. I declared social network bankruptcy around the time of Orkut and haven't gone out and found everyone I know on any social network site since. What we need is an underlying identity system to make this all less work (and to stop me seeing the same set of photos three times in a row in Messenger Social because the same person posted them on Flickr and syndicated that to Facebook and Live... Although at least twitter syndication onto Facebook helps with twitter vanishing off live!
Tuesday, August 3, 2010 12:32:38 AM (GMT Daylight Time, UTC+01:00)
I think we already have interest networks, each person their own individual one.

It's in their head. It's often unrecognised. They've been around for a long time.

The cloud/computer versions are first stumbling attempts. Based on a minimal and unexpressive boolean linkage. They're useful to a degree, a small degree.

When cloud/personal-computer versions get more sophisticated I would hope that most people each have their own. Not some commodity managed and traded by people who cannot possibly have your individual interests at heart!

Agreed FB is not a good basis, but neither is anything else that I've yet seen.
Mike Gale
Tuesday, August 3, 2010 1:11:05 PM (GMT Daylight Time, UTC+01:00)
Surely it depends if Facebook succeed in getting people to tag (or classify) their social links.

There are ways to do this on FB, but it doesn't promote it much. But someone could write an app. which could somehow classify the relationship between two people based on things you tell it, even what your interests are etc. Then it could export that knowledge to widgets on the Engadget site.

Why not even make this a query option on the widget : "show me things that work-colleagues like", or "show me things that geek buddies like" or even "show me places that friends with higher than 85% similarity to me on the RockYou survey of "best things to do on my day off" like"
Tuesday, August 3, 2010 5:29:47 PM (GMT Daylight Time, UTC+01:00)
Excellent post and good discussion starter. If the web is any example, I expect to see an explosion of social graphs, not an AOL-like walled garden. I think we may see user show up to a website with a suitcase of their friends interests...
Cheers, Joe Glynn
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