Given how much user activity goes on every day on Facebook, the company has to be working on some kinds of recommendation technologies. Charming invisible robots that say, “If you like this, then you’ll like that.” Full-time Facebook watcher Nick O’Neil thought he spotted one in the wild this morning, but his readers make a convincing case that he was wrong this time.
The feature O’Neil wrote about appears to be nothing more than the latest FriendFeed rip-off: truncating repetitive activities. (Ex-Googler Paul Buchheit’s FriendFeed is like a Facebook R&D lab without stock options.) Whether Facebook is doing more than that publicly or not, you know they have to be working on recommendation behind closed doors.
O’Neill’s AllFacebook blog is a great place to get the scoop on what’s happening on the social network. Here’s an image he posted this morning, from a reader named Luka Kladeric.
O’Neill wondered whether this feature might give the user an option to view other items from the same or other users that Facebook deemed similar to the original post. I say I’m drinking coffee and Facebook shows me a movie, a picture and another message about coffee from one of my friends this morning. That would be pretty awesome for us as users and it would increase ad impressions for Facebook.
More likely is the explanation offered by AllFacebook readers, that this new feature is just a way to scrunch up items that are basically the same so users can’t spam their friends’ newsfeeds and so that newsfeeds are more pleasing to scan down. In other words, in the image above, the two-headed person on top probably posted about “besplatno-ing” like four times in a row. Facebook decided to show just one of those messages and add a link to view the rest.
That’s how FriendFeed does it and it works really well. This seems like a plausible explanation of this screenshot, but it’s also a real lost opportunity. Facebook’s corny “your friend is a fan of this advertiser’s stuff” may be more creepy than compelling – but automated recommendations of all types of items could be great.
We’re big fans of recommendation technologies here at ReadWriteWeb, from relatively simple “people who like X also like Y” to more complicated algorithms. The systems are fun to learn about, but the fact of the matter is that recommendation doesn’t have to be hard. The hard part is amassing enough data and interested people to be able to make recommendations. Facebook has plenty of data and people, though its labyrinth of privacy restrictions might complicate things a little.
So if this isn’t it, and we suspect it is not, we sure do hope that Facebook will soon surface the recommendation technology we assume they are working on behind the scenes.
