Is FriendRank Next?

I used to differentiate between the Old School of Research and the New School whereby one started a research project. Old School info pros like me, who learned our trade before the days of the web, still catch ourselves framing a research project around what databases we subscribe to. "Let's see ... I can use Dialog's MAP command to pull out that information."

New School info pros head directly to the web. Yes, they'll search a fee-based online service, as long as it's as intuitive and as easy to use as Google. Yet I found it quite illuminating when two longtime info pros told me that they no longer considered Dialog (in its current iteration) to be relevant. They had no interest in learning an obscure search syntax and felt that they could find enough content through other, more familiar web tools.

These are the New New School info pros, for whom Facebook is home. Those in the Millennial generation have always been able to text their friends and have always relied on Wikipedia as an authoritative source. In fact, I think of this cohort as the Collaborative generation. They bring remote friends into any situation through their mobile devices, they share their perspectives on whatever they rely on, and they pay little attention to hierarchy. The Millennials have already rewritten the standards for gathering and evaluating the information required for a significant decision. They head to where there is a discussion of that topic; they poll their colleagues; they Ping someone who frequently Twitters about the subject.

One response to this collaborative mindset has been the emergence of a new generation of web finding tools that focus not on being comprehensive (that's what Google is for, right? ) but on finding the portion of the web that others have found to be the most helpful. Instead of wanting to see the World Wide Web, we're more interested in the friend-of-a-friend (or FOAF) web. Two recent examples include Google's Social Search and, both of which are aimed at helping searchers find more of what others find useful.

Google's Social Search has raised the eyebrows of those concerned with privacy; the premise behind Social Search is that you may be especially interested in what people in your network are saying about the topic you are researching. How does Google know who's in your network? This is what reminds some reviewers of Big Brother-or possibly even the Borg.

To participate in Social Search, you sign up at www. Then, with your permission, Google pulls your contacts from any social network you have included in your Google profile, people in your Gmail chat list, people in your Google Contacts groups, and-most interestingly-any immediate contacts of those people. It scans for web content from those people, everything from restaurant reviews to blog postings, tweets, and YouTube videos, and surfaces that content at the bottom of the search results page.

I believe that most info pros' first reaction to Google Social Search mirrors their location in the Old School/New School continuum. We of the Old School react with either, "Ack! There goes my privacy!" or "Why in the world would I care about this?" Millennials, on the other hand, are more likely to see this as a natural extension of their native information-filtering behavior. Many of their interactions are within an extended but closed network of Facebook friends. To be able to search the web-with that same FOAF filter they are accustomed to in their interactions with their network-is seen as a positive development.

OneRiot takes a similar approach of paying attention to what others have pointed to, by applying a Twitter filter to the web. Instead of indexing all content on the web, the OneRiot spider only indexes pages that have been linked to in Twitter. While this initially sounds like an arbitrary limit, it serves as a way to highlight new pages or pages on an emerging topic that have not yet been well-indexed by the major search engines. Again, this is a way to limit a searcher's experience with the web to only those pages that are calculated to be of interest because of network analysis.

I expect to see far more of these kinds of web search tools as the nonstatic portion of the web becomes more content rich and as search engines find that the algorithms that worked well in Web 1.0 aren't scaling well to the collaborative web.