The key feature that would go along with this is that then it would enable LinkedIn to intelligently recommend the best possible introduction path.

Another important feature that goes hand-in-hand with this is for the 1st-degree contact to choose the route if there are multiple 2nd-degree people who can get to the 3rd-degree person. Of course, if the feature I described above were implemented, this wouldn’t be as needed, since it would already be choosing the strongest path. As it is now, I’m not 100% sure, but I think it’s basically random – not sure how it could be anything else.

The behavior variances in linking work along community and cultural lines too – early-stage VC’s might be more willing to hear from 3rd-degree people with the right approach than operating executives would; I would be more inclined to add people to my network when I’m looking for a job.

I’ve long hoped for LinkedIn to add some calibration to the network and look forward optimistically that too. If there were a way to “price” those rankings meaningfully, so much the better (e.g., on eBay, you must transact in cash to rate a user). In fact, LinkedIn already has a pricing mechanism – if you ask me to introduce you to someone in my secondary network, and I agree, I am spending relationship capital on both you and the intermediary contact. Whereas if I say, gee, I know Warren Buffett is in my extended network, but I decline your request because the guy who connects us is someone who I know only superficially and is a promiscuous linker, that tells you something too. Limited numbers of introductions is also a form of pricing (though probably one that’s less useful), and there are other ways to extract implicit valuation of contacts (e.g., “send a holiday card to selected members of your extended network”).

LinkedIn would do well to use – and create interesting leverage and visualization of – this kind of data.