Aardvark & Google: The Efficacy of Social vs. Traditional Web Search
February 4, 2010
Computers are always processing information, but they don’t know how to process knowledge… It is always humanity that generates meaning.
This is why I now believe that the primary goal for technology should not be replacing human intelligence but, rather, facilitating human interaction.
Damon Horowitz, “Why Machines Need People”
From Social Data to Real Results: Taking the Initiative, Finally
A few weeks ago we wrote about Aardvark in the context of people as real-time information.
The amount of information in people’s heads positively dwarves the amount of information online, even today.
This time we’d like to hat-tip Aardvark for its transparency and research-savvy. It recently released an impressive paper entitled: “The Anatomy of a Large-Scale Social Search Engine.”
Popular social applications—especially those with real-time capabilities, location-awareness, or both (Aardvark, FourSquare, Brightkite, Blippy—and scores of others) are a veritable gold mine of user-generated information about everyday human behavior—social, physical, economic.
It takes someone to view creatively, organize intelligently and make transparent the aggregate results, but this information should be used to manifest and explore latent ideas that have real implications for the way we live.
Aardvark vs. Google
Aardvark conducted a test alongside Google search to assess the relative efficacy of its own social search engine from a user-experience standpoint. Aardvark users opted into “an experiment” where they also reformulated their question as a keyword query to Google.
(The paper acknowledges possible bias in favor of Aardvark; current Aardvark users, who already believe the service is helpful, were recruited—and it’s reasonable to expect that, in some cases, Aardvark was chosen because an initial Google search was unsatisfactory. Still, even considered independently, the values for Aardvark are impressive.)
Engineered Serendipity
Sharing a little from Aardvark’s recent paper, which primarily discusses the algorithm underlying its revolutionary platform, we thought that the way people are “indexed” and matched according to knowledge needs and abilities was rather fascinating.
Aardvark computes user matches along the following axes:
- Social connection (common friends and affiliations)
- Demographic similarity
- Profile similarity (e.g., common favorite movies)
- Vocabulary match (e.g., IM shortcuts)
- Chattiness match (frequency of follow-up messages)
- Verbosity match (the average length of messages)
- Politeness match (e.g., use of “Thanks!”)
- Speed match (responsiveness to other users)
Aardvark on TEDx: Why Machines Need People
Below is a TEDx video of Aardvark’s Damon Horowitz discussing his history as an AI developer and his arrived-at conviction that “the primary goal for technology should not be replacing human intelligence but, rather, facilitating human interaction.”
To give you an example: we have systems today which can search through all news articles that have ever been published, and find just those that are about the recent earthquake in Haiti. Then we have semantic technologies that can read through those articles, pull out all the facts and figures, and tell you what happened—they can tell you what Obama’s reaction was to the Earthquake in Haiti. Well, that’s kind of incredible.
But I can’t then turn around and ask my computer: “Hey, computer, how does that compare to other presidents’ reactions to other natural crises?” I can’t say, “Would you please explain to me how foreign aid works?” I can’t brainstorm with my computer about creative ideas how I could get involved and how I could help.
Damon Horowitz, “Why Machines Need People”
Header image courtesy of deapeajay’s flickr, (cc) some rights reserved.














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