I feel inclined to comment on the notion of Social Search and it’s purposed take-over of how people search on mobile devices.  While the concept has extreme potential, it won’t be realized until several fundamental aspects are addressed- aspects that will take time to evolve and make themselves known.

Aardvark recently published a comprehensive research paper entitled “Anatomy of a Large-Scale Social Search Engine,” whereby it delves into the conceptual aspects of social search and how it fundamentally differs from traditional search.  The research mirrors that of Google founders Larry Page and Sergey Brin’s “Anatomy of a Large-Scale Hypertextual Search Engine,” that outlines the theory of Google PageRank and the ideas that have made Google the dominate search engine it is today.

Aardvark’s research describes traditional Web search as a “library” approach, whereby results and answers are found in existing Online content.  Social search from the likes of Aardvark, and the droves of other startups eeking their way into the marketplace for that matter, describe themselves as having a “village” approach- whereby answers arise in conversation with the people in your social network.

I agree with the self-proclaimed benefits of social search through the eyes of Aardvark, which are that users can ask questions in a natural language — without having to speak in keywords — that content is generated “on-demand” tapping real people who can give more informed results, and that the surrounding ecosystem is fueled by the so-called “goodwill of its users,” but therein lies the problem.

Getting answers from real-people takes time, as users of ChaCha, KGB and even Aardvark can attest to, and while the answers may be more relevant and comprehensive than what a user can find using traditional search, it doesn’t create a user-experience that’s sustainable, and therein lies yet another problem- scalability.

Unlike traditional search that’s driven by algorithms and thereby are computational in nature, social search relies on a human-aspect, which is inherently hard to scale effectively for growth.  For each query that comes into the system, a person has to respond and react, leaving no automation to help bolster continued growth.  Both ChaCha and KGB have had problems figuring out how compensate a work-force of “answerers,” while aligning themselves for the growth they’re experiencing.  This is a scalability issue that Google doesn’t have to worry about.

Adding humans to the mix also makes me question the accuracy of the results behind social search.  When I search using Google, I rely on the fact that Google’s algorithms will find the most accurate and relevant results based on what I’m looking for.  When you receive an answer via social search, you have no idea of the level of accuracy in the result.  Humans are prone to errors, computational algorithms are not.

While I may be way off base, or don’t see the so-called “big picture” when it comes to social search, I still come to the conclusion that the concept has a long way to go before becoming a viable option for consumers in the long-term.  I’d love to hear some differing opinions on the subject, so feel free to sound-off in the comments.