You can't visit a webpage these days without it begging for a compliment: Like us! Share us! Follow us! Social media promotion is one big reason why--just look at The Washington Post , for example, which seems intent on replacing its brand name with the Facebook  logo, and barely refrained from slapping a "Like" badge on everything from its user agreement policy to its copyright acknowledgements. But viral promotion isn't the only reason.
Increasingly, social media is impacting search-engine rankings. By mining data from social networks such as Twitter  and Facebook, the world's largest search engines hope to make results more relevant for users. Just as you're likely to trust a restaurant or movie recommendation from your friend over a recommendation from a stranger, Google  and Bing have realized that results your friends and followers have "Liked" or tweeted might be more relevant than any algorithm could ever decide.
But according Stefan Weitz, director at Bing, which only yesterday released  a slew of improved social features, the search giant won't have to depend on the Facebook's "Like" button forever, even if it takes years to better integrate social data.
"There are more signals than just 'Likes,'" Weitz tells Fast Company. "There are tweets, check-ins--when I'm at Spur restaurant in Seattle, and I say it's the best lamb tartare and post that on Yelp, that's a signal as well. There's a world where all these social and personal signals--whatever you want to call them--are consumed and indexed and made sense of."
For now, however, the social search experience is very much an annotated one. Currently when you search on Bing and Google, you'll see regular results mixed with social results, which are each marked with a small indicator of who shared the link. A search for "Fast Company" on Google, for example, will return a number of articles shared by my followers on Twitter. On Bing, results will show which of my Facebook friends "Liked" a particular link or site, and how many "Likes" a particular source received. All these annotations are supposed to call out to us: click here--trust your social network!
But as Weitz explains, it's still very early on in the process of incorporating social data with search. "'Likes' are a good proxy today for expressing your appreciation or some level of opinion, but there are others. The question really is which of those are going to gain traction," he says.
In the future, social data is likely to be integrated in a more intuitive (and less explicit) way, meaning search engines--unlike websites--could avoid becoming riddled with Facebook "Like" badges. (Thank heavens.)
"It's not ten years, not five years away, it's a couple years away--tops--where social is literally so imbued into the experience that it's just another ranking factor like anything else," says Weitz.
In the meantime, would you mind "Liking" this story?
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