While Google announced its own independent “liking” feature in the form of the Google +1 button several weeks ago, Microsoft competitor Bing announced on Monday that it would be directly incorporating Facebook “like” data into its search rankings. For the logged-in Bing user, a result that may have originally appeared lower in relevance will gain a boost toward the top simply by the virtue of having been liked by the user’s friends. In this gutsy move, Bing has divorced itself from the simple “search engine” label and is now something more like a community opinion aggregator, specifically relevant to the individual utilizing it.
The question is, how useful is this going to be to the average searcher? While I like and respect my Facebook friends, chances are I’m not going to be interested in what every one of the 400+ party acquaintances, elementary school buddies and past coworkers think that I should be looking at. While Facebook has some rudimentary measures in place to weigh whose profiles are more important to yours and vice versa, I’m not sure if this weighting will translate well to said friends’ opinions of search results. However, opinion harvesting is not simply related to your own friends list; Microsoft is touting this measure as a triumph of “collective IQ,” stating in its official blog post about the move that results will also be influenced by the likes of those who are not in your network. It’s the wisdom of the crowd, extended to large-scale. Popular recipes, for example, are markedly prominent when their ingredients are searched for:
While I’m unsure of the specific implementations of this move, such as incentivizing users to actually stay logged in to Facebook while they browse, I’m not sure if this is the death of objective search results. Google has always based its rankings at least partially on outside approval, and who’s to say that the average Bing user won’t benefit from the recommendations of their peers?
One intriguing and complex aspect of this new method will come in the form of “enabling conversation,” wherein Bing attempts to determine who (if anyone) in your friends network is most qualified to help make a decision or provide advice. If you’re searching for a certain city, for example, those in your network who live or have lived in said city will be suggested to provide recommendations. This is a useful but potentially enormously complex system involving huge amounts of data gathering, one whose practical applications remain to be seen when tested by user interaction.
With Bing and Facebook announcing this unprecedented merger of sociality and search, Microsoft’s rebranding of Bing as a “decision engine” instead of a “search” one is well-chosen. While results may be skewed toward the populist instead of the purely informational, there is unquestionably a specific niche for this kind of service, and I’ll be surprised if the coming months don’t usher in an even closer and more integrated relationship between the two.
Posted on Thursday, May 19th, 2011
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