Teaching, learning and research have always been social activities involving heavy reliance on trust, reputation and brand awareness., and these social aspects of information seeking behavior grow more prevalent every year. This natural tendency to seek reliable, community-validated information sources has traditionally drawn people to libraries for two reasons.
First, librarians have a reputation for professionalism, reliability, honesty, intelligence and respect for individual privacy. Second, librarians answer so many reference questions that we serve as a communal memory and reputation monitoring service. In other words, as patrons tell us their opinion of certain books and information sources, we listen and reflect that information back to other patrons. However, we primarily distribute this information anonymously in aggregate form and maintain strict privacy when it comes to individuals’ opinions and browsing habits.
Two recent stories illustrate the ways in which the Internet with its mountains of data and processing power exceeds the abilities of the average reference librarian in some respects and lags far behind in other respects.
Dave Winer’s recent blog post on new social search features at Google makes it clear that large Internet companies have certain advantages over humans when it comes to sorting and filtering online metadata about the quality and reliability of other data sources. If you choose to share your various online profile URLs (Facebook, Twitter, Flickr, etc.) with Google, the search giant will query those services to see to whom you’re connected. Using this data, Google will assign more weight to results from your friends and trusted sources. Bear in mind though, this feature is still in beta. However, while social networking services are creating useful new metadata about reference resources that might make research easier, they’re also exposing our privacy in new and alarming ways. According to this story on The H Security site, researchers at iSec Lab have hypothesized that it’s possible in theory to uniquely identify someone over the web by comparing their browsing history to a list of postings and affiliations at Xing, a popular social networking site.