movies, musicians, political views, regions, schools, sports, sports teams, and TV shows) and 16 types of public places (bars, bookstores, brunch places, cafés, gyms, hair stylists, hotels, landmarks, movie theaters, museums, parks, restaurants, schools, shopping malls, supermarkets, and theaters).
You can refine your search to results “liked” by you, your friends, your family members, or specific friends; to specific cities; or to places you, your friends, or your family members have visited. (Facebook’s information about your whereabouts comes from check-ins and the geotags on your photos.)
Graph Search has a few shortcomings—which is to be expected, considering that it’s an early beta product. The biggest problem is probably this: the results are only as good as the information users have given to Facebook. If you’re a musician but you haven’t made that clear in your profile, you’re not going to show up in searches for musicians. If you were ever snookered into “liking” something that you don’t actually like (which happens all the time, according to tech blogger Steve Cheney), it will skew the results of your friends’ searches.
Other problems also worry me. It’s not clear how results are ranked within Graph Search result pages, and how much I should trust them. Why was Kepler’s at the top of my bookstore search? Because it was visited by more of my friends than any other bookstore on the list, or because they visited it more often? Or because Kepler’s paid Facebook for the placement? That last one isn’t a possibility right now, but it might be in the future.
On top of all that, there are a lot of queries that yield only one or two results or none at all (e.g. vegetarian restaurants in San Diego liked by my friends), presumably because my network is too small. Yet I have more friends than most Facebook users. So I’m wondering how useful Graph Search will be to people with the average number of friends (around 230) or fewer. It seems clear that in a Graph Search world, it’s advantageous to have more Facebook friends, the better to draw on their likes and experiences. But by definition, the more friends you have, the shallower each connection will be. I’m not sure that’s the direction anyone wants to go in their social networking activity.
According to biographer George Dyson, the pioneering computer scientist John von Neumann refused to predict how the electronic computer he was building at Princeton in the 1940s would be put to work. The machine was “so radically new that many of its uses will become clear only after it has been put into operation,” von Neumann said.
He was right about that—and I think the same thing is true of Graph Search. It will take a while for Facebook users, and Facebook itself, to figure out the software’s most interesting applications, but they will be many and profitable. Facebook just evolved from a toy into a tool.
