What is Intelligent Scoring?

So, we’ve identified the problem.  Lots of information.  We realize that the more stuff there is, the harder it is to sort through it and find the really good stuff.  The same is true with people.  The more people there are ”in a room”, the harder it is to identify with whom you want to spend your time.

What we need is something that does this work for us.  One solution would be to hire an army of editors (or moderators) to sift through content or “work the room” for us.  Clearly, they could identify the good content and the best players in the game, right?  Well … maybe … assuming that they are significantly credible and proficient in the concerns of the community to represent us.  But how do you know that they will make good judgments, unless you’ve already got a mechanism in place to select them out of the crowd?  Pretty significant catch-22, since that’s what you’re “hiring” them to do in the first place.

We’ve already talked about the phenomenon of social networking.  As the Internet grows, it has begun more and more to resemble a giant democratic community.  Sites are emerging every day that leverage the power of the democratic process to understand what is valuable — check out MySpace, Digg, Flickr, Del.icio.us and Topix, just to name a few.  This is because those who use the net all over the world are feeling the pain that we’re describing — sifting through the noise to find the value.

I propose that we leverage this democratic process.  Give the people the vote.  Instead of trying to come up with an army of editors, let’s use the army of people already in the room.  We don’t have to know them by name or have them on the payroll to glean a wealth of valuable information from observing their interactions.  That’s where Intelligent Scoring and our engine come in.

Lots of efforts out there are counting number of views and downloads, lots are giving members of the community the opportunity to vote for what they like, but these are only a couple parts of a much larger picture.  Think bigger.  The idea is to observe the behavior of the community (to collect the vast amount of data that’s right in front of us, but that is easy to overlook), and to be smart about interpreting it (to pull from the data valuable conclusions that can be drawn about the members of and content in the community).

This solution requires automating the process.  There aren’t enough editors in the world to sit around watching and interpreting interactions.  Who could afford to pay for all that?  Instead, let’s use the computer.  That’s what we built it for, right?  If you’re surfing your favorite online community, and behind the scenes there’s an engine observing your behavior — along with the behavior of everyone else in the community — then you have a powerful mechanism in play from which to draw conclusions.  Couldn’t these conclusions be about which content is the most valuable or about which members are the most significant?

Our goal has been to create just such a mechanism — to do the hard work of causing the good content to rise to the top, and to identify the best members of the community.  We call this mechanism the “Content Valuation Engine”, or CVE.  It is the heart of the idea of Intelligent Scoring.

Technorati tags: web 2.0, myspace, del.icio.us, flickr, topix, digg