I like Paul Knag's post on Creating Online Identity TrustRank today, so I'm going to write about it.  Kinda wish I had Paul on the WAA Social Media Committee at the Web Analytics Association, because he could make a contribution to the work we're beginning to define Social Media Standards.

Paul talks about the Social Graph by citing a paper by Brad Fitzpatrick and David Recordon, getting into the level of documentation that I'd like to see for a Social Media Standard (IE: Trustrank or Friendship):

"…global mapping of everybody and how they're related, as Wikipedia describes …."

"…For developers who don't want to do their own graph analysis from the raw data, the following high-level APIs should be provided: ¶

1. Node Equivalence, given a single node, say "brad on LiveJournal", return all equivalent nodes: "brad" on LiveJournal, "bradfitz" on Vox, and 4caa1d6f6203d21705a00a7aca86203e82a9cf7a (my FOAF mbox_sha1sum). See the slides for more info.
2. Edges out and in, by node. Find all outgoing edges (where edges are equivalence claims, equivalence truths, friends, recommendations, etc). Also find all incoming edges.
3. Find all of a node's aggregate friends from all equivalent nodes, expand all those friends' equivalent nodes, and then filter on destination node type. This combines steps 1 and 2 and 1 in one call. For instance, Given 'brad' on LJ, return me all of Brad's friends, from all of his equivalent nodes, if those [friend] nodes are either 'mbox_sha1sum' or 'Twitter' nodes.
4. Find missing friends of a node. Given a node, expand all equivalent nodes, find aggregate friends, expand them, and then report any missing edges. This is the "let the user sync their social networking sites" API. It lets them know if they were friends with somebody on Friendster and they didn't know they were both friends on MySpace, they might want to be.

But more generally, for developers, enabling new kinds of apps we haven't been able to think of yet.

What's interesting too.. is that Brad Fitzpatrick is trying to do what they're talking about above:

"…As of 2007-08-16, a lot of the above has already been prototyped:

1. got the data to 5 large social networks, modeled them in the graph
2. prototyped working implementations of the APIs above (lot of room for performance optimizations, caching, and parallelism, but wanted to get correctness first)
   1. Was able to find all my missing LiveJournal and Vox friends, based on my relationships elsewhere.
3. start of a Firefox plug-in to work with MySpace
4. start of a website to let users declare extra public nodes, node equivalences, and relationships that aren't otherwise automatically picked up (website to include fun stats and widgets, as enticement for users to go there, as well as browser add-on downloads, to sync different sites, if they choose to do that)."

I liked the part that Paul Knag brought in when he defined how trust is being measured now:

"…There are several models of trust already in existence, all of which are too simple to handle the complex requirements of identity and trust management, given the incentive which exists to abuse such. Some existing techniques include approaches such as:

1. Use of Captchas
2. Use of email address validation
3. Use of SSN Validation
4. Use of physical address validation (ie. Google Local)
5. Public display of account history (Ebay, Forums, Wikipedia)
6. Tracking and display of IP address (Wikipedia)
7. Friending schemes (MySpace, FaceBook, LinkedIn)
8. User empowered TOS monitoring (Wikipedia, YouTube)."

Not only do I like the quality of thinking here - but the definations are useful as taking off point and I see each defination that comes out of the Social Media Committee as having, as much as possible, this level of defination.

In that sense, I see the Social Media Standards doc that we'll come up with as 1000 miles apart from the Web Standards Doc the WAA Standards Committee came up with a couple of weeks ago:

"…New Standard Definitions Announced

Thursday, August 23rd, 2007 —WAA Standards Committee Co-chairs Jason Burby and Angie Brown announce the publishing of standard definitions for 26 foundational web analytic metrics covering the areas of visits, content and conversion. This is the result of a collaborative effort between members including vendors, agencies, practitioners and thought leaders. The new definitions provide consistency of the most widely used terms across the analytics industry. Learn more about the Standards Committee and download the 26 new web analytics standard definitions.