Liad Agmon, CEO of Delver, says that the site connects information about a user’s social network with Web search results, “so you are searching the Web through the prism of your social graph.” He explains that a person begins a search at Delver by typing in her name. Delver then crawls social-networking websites for widely available data about the user–such as a public LinkedIn profile–and builds a network of associated institutions and individuals based on that information. When the user enters a search query, results related to, produced by, or tagged by members of her social network are given priority. Lower down are results from people implicitly connected to the user, such as those relating to friends of friends, or people who attended the same college as the user. Finally, there may be some general results from the Web at the bottom. The consequence, says Agmon, is that each user gets a different set of results from a given query, and a set quite different from those delivered by Google.
In the released version, users can link Delver to profiles stored on MySpace, Facebook, Blogger, Flickr, LinkedIn, YouTube, hi5, FriendFeed, Digg, and Del.icio.us. The company says that it plans to add support for other social sites in coming months. To build out a profile further, a user can enter details such as profession, education, and location. Users can also connect to people on Delver who bring up interesting search results.
In my experiments with the early version, I found that my personal network alone didn’t produce enough results to make the service useful. It seems that early adopters will need to focus on building up connections to other Delver users, or perhaps to bloggers who tend to write about topics of interest to them. I continue to think that Delver is an interesting idea, and I look forward to seeing what the site looks like once it’s collected more social data about its users.