As beefcake points out in a recent post, there is significant need for effective web page filtering. Due to the web’s monolithic size and the dynamic nature of its content, effective filtering becomes very difficult. In class, we focused on exploiting the hyperlink structure of the web to rank pages relevant to a query. Though this is a powerful, proven method used by Google and other search engines, it confines the user to using queries to explore the web. While this helps users locate relevant items, it is not particularly useful for discovery of things that they aren’t yet aware of but may find interesting.

A few sites are now offering a clever, more personalized search approach. These systems take advantage of the power of online social networking to filter the web’s content and help users discover new and exciting things. Digg, for example, relies on users to submit articles they find on the web. These stories are then voted on by other users, which helps determine whether or not they get promoted to the main pages. In addition, users may befriend others to view the stories they have submitted or voted on. In her article, “Social Networks and Social Information Filtering on Digg” Kristina Lerman examines how these sites have transformed the web into a participatory medium. These sites enable users to evaluate content and share their opinions with others across the web. This represents a shift in the web usage paradigm. Rather than merely querying the body of information on web pages, users are now assuming an active role in the creation, evaluation, and distribution of online content.

In an effort to examine the effectiveness of Digg as a recommendation system, Lerman examines the effects of using social networking for content filtering. She determined that users are more likely to signify that they like, or “digg,” stories their friends submit. Also, user’s statistically digg stories that their friends also digg. While these properties indicate reasonable social filtering, Digg’s system is not perfect. The characteristics of Digg’s social network can result in overrepresentation of a relatively small minority. This is because of the network effects experienced by the top users. Those with the largest network of friends are ideally positioned for achieving a large numbers of diggs on their future posts. Also interesting to note is the tendency of some users to add large numbers of friends. This could lead to some herding effects seen with information cascade. Users may be more inclined digg content merely because it is popular among their friends.

Del.icio.us is another interesting social networking system which relies on its body of users to bookmark content across the web. In addition, it allows users to tag the content using keywords. This adds useful metadata which categorizes the content and allows users to browse information more efficiently. This accomplishes the filtering suggested by beefcake, and helps avoid the issue of the web site creator intentionally misrepresenting the information for personal gain by delegating this responsibility to a larger, hopefully unbiased user base. Though it is far from perfect, social filtering is a promising technique which offers some unique advantages over traditional query-based systems.