Based on my Likes, Likester thinks I might also be fond of Megan Fox (duh), George Lopez (definitely not), The Cheesecake Factory, Batman, and the Dalai Lama. For me, I’d say the recommendations are only about 60 percent accurate. Your mileage may vary.
It will also tell you what your friends might or should like, and allow you to push its recommendations upon them whether they want them or not.
Of course, those are just the features Likester tosses out there to get people to use its app, which it labels a “game.” Likester’s real purpose is to allow Facebook advertisers to target people who might already have an affinity for their products, even if they don’t even know it yet. You can slice and dice the Like data in all kinds of ways – affinities, location, yadda yadda – to create specifically targeted ad campaigns. There’s a video about this if you’re really interested.
The trouble with this model is that when you look at it closely, the data gets a little weird. For example, people who say they like Apple have an inexplicable fondness for music, products, and celebrities based in Brazil.
As BusinessInsider points out, some of the data correlations are downright screwy. For example: Yankee fans are 15 times more likely to like the Red Sox, and vice versa. That might be true in an alternate universe, maybe, but not on this planet. The conclusions I’d draw from that info nugget are a) both groups like baseball more than most bipeds do, and b) there is probably something wrong with Likester’s algorithms.
Farming your Likes is what Facebook is all about these days. Unlike status updates, photos, videos, and other things you voluntarily share on Facebook, you have no privacy control over your Likes. They are public information, accessible by anyone with a Facebook account – or, like Likester, the wherewithal to turn them into a product.
You are what you Like. So be careful where you click.