FriendRank

· The Power of Many

Like most normal people, I was just having an interesting telephone
conversation with a friend of mine (at 2am) about Google, Yahoo,
Friendster, on-line marketplaces, approximate searches, and some
secret stuff. Along the way I got to thinking about some of the
fundamental similarities between Google (those who mapped the
relationships among web pages and put them to use) and Friendster
(those trying to map human relationships and put them to use).

It occurred to me that Friendster needs FriendRank. Like Google’s
similarly named dead
technology, PageRank, think of FriendRank as a way of providing a
measure of influence among “friend nodes” in a social network.
Imagine, for example, that Howard Dean wants to convince me to vote
for him. He can either advertise in the hopes of reaching me, or he
can be a savvy Internet sorta guy and try to use my social network
(thru the Internet, of course) to do the job.

At first you might think okay, that’s easy. You just need to find
the shortest path thru the network from Howard Dean to me. Then you’d
figure out who along the way he needs to contact to try to get to me.
Well, maybe. Social networks aren’t that simple. They don’t always
use the shortest path–at least not in the “six degrees of Kevin
Bacon” sense. Often times they use the most well lubricated path. Or
the path that may result in reaching the greatest number of people who
are “close” to me. Or those that have more influence with me in
matters of politics, as opposed to something complete unrelated like
cat grooming.

You get the idea. Like PageRank, it’s a multi-dimensional measure
that could prove to be quite powerful if applied properly. It’s like
a routing problem with different dimensions involved.

FriendRank would quantify that stuff. It’s the algorithm used to
find paths of social influence in various contexts, for various
purposes, and in varying networks. Or maybe it’s the value that
algorithm produces for a given set of inputs. Either way, it’s the
idea that counts, right? Initially. Then comes the
implementation.

Now, if you go search for references
to FriendRank
, you’ll see a few. So this term (and idea?) isn’t
exactly original. But some of the real possibilities just clicked
for me about 10 minutes ago, and believe me, this example is
the tip of the iceberg. Some of the discussion here is
really, really missing the point. So try not to get sucked into that
void.

(Yes, I’m purposely not saying a lot of what I could yet. It needs
time to percolate…)

On a semi-related note, it’s too bad there’s no Friendster web
service API I can use to get the data needed to prototype this, huh?
That could be a lot of fun. Or really frustrating, as most hard
problems are… :-)

On the other hand, Friendster is not a necessary component
in the equation. (Or Tribe.net, or LinkedIn, or…) It’s just damned
convenient since it’s big and centralized. If I could get access to
enough IM buddy lists, blogrolls, and so on, it’d be doable
but much, much harder.

Okay, bed time now.

[Jeremy Zawodny’s blog]