The Hidden Gems that Social Graphs Bring to Light

Rate this post claims to be able to predict which startups are more likely to succeed.  While I hesitate to endorse the idea that their predictions are accurate, the methods are quite interesting.  According to the NY Times that introduced YouNoodle from stealth:

their algorithm uses sophisticated modeling pertaining to how social capital and networks can affect an organization’s performance.

They also say that they are focusing in general on assessing the experiences and social and business contacts of entrepreneurs who start a company, and on how the entrepreneurs within that company might fit with one another. They will not disclose precisely what factors they use to predict a start-up’s success, or how their algorithm processes those factors.

If you visit the site, YouNoodle is still not revealing all, but it looks a lot like a social network for startups.  Here’s the entry for startup SnapTalent, for example.

What does all this have with the likelihood for success?  I can but speculate, but my speculation goes something like this, and is based on my own experiences as an entreprenuer.  I suspect the Social Graph piece is attempting to determine whether the founders are connected enough to reach critical mass in getting their ideas noticed.  That fits well with “using sophisticated modeling pertaining to how social capital and networks can influence an organization’s performance.”

Can a startup succeed without social capital?  I doubt it.  After all, they have to get the word out somehow.  I’ve suggested in the past that maybe startups ought to insist on having a top-notch blogger on staff, but these guys are taking it another step up altogether.  They seem to insist that a startup be sufficiently linked in to the right groups of people.  It’s a fascinating premise.  As we interact with the web, we leave behind our footprints.  Suitable forensic research can determine from those footprints something about our networking and sales skills.

A lot more is likely possible from a detailed analysis of Social Interactions on the Web.  LinkedIn recently announced they were going after the investment community.  Tim O’Reilly described the service thusly:

While the service isn’t going live for several months, Mike outlined the core of the value proposition, which I could sum up as a Web 2.0 version of the Gerson-Lehman Group‘s expert network. Gerson (or GLG as it is often called) has made a splash in investment research by assembling a network of experts on virtually any topic. Subscribers pay a hefty subscription fee for access to that network.

Think about it.  If it’s true that it isn’t what you know but who you know, the Internet could be the ultimate wealth enabler.  This kind of information is very new in the world.  Even ten years ago, what mechanism would have been available to assess from afar how well networked various people are?  Social Graphs are revealing new and compelling hidden gems of insight that can be mined for various purposes.

What other uses can such information be put to?

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