The social networking goliath has just won a patent covering a certain type of search algorithm, one that is largely based on the interests and clicks of a user's friends and friends-of-friends.
Specifically, the patent is for "ranking search results based on the frequency of clicks on the search results by members of a social network who are within a predetermined degree of separation."
The patent continues, "Search results, including sponsored links and algorithmic search results, are generated in response to a query and are marked based on frequency of clicks on the search results by members of social network who are within a predetermined degree of separation from the member who submitted the query. The markers are visual tags and comprise either a text string or an image."
The listed inventors are Chris Lunt, Nicholas Galbreath and Jeff Winner. The patent application was filed almost six years ago; we're uncertain how much this technology plays into Facebook's current business and search strategies. Still, the patent calls into question whether users click -- or buy, or watch, or behave in other ways -- like their friends and peers do.
What we do know is that Facebook search has been a priority for the company since its redesign earlier this year. At that time, the search bar on the site was given a prominent new position, and several under-the-hood upgrades rounded out the Facebook search experience.
We've also seen a lot of sidebar ads and recommendations lately centering around what a user's friends like within the site. All in all, the patent seems to line up with Facebook's general mission to explore (and profit from) the synapses and connections within a social network.