Social Networks and Social Information Filtering on Digg

نویسنده

  • Kristina Lerman
چکیده

The new social media sites — blogs, wikis, Flickr and Digg, among others — underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide which stories to promote to the front page. Digg users can designate other users as “friends” and easily track friends’ activities: what new stories they submitted, commented on or read. The friends interface acts as a social filtering system, recommending to user stories his or her friends liked or found interesting. By tracking the votes received by newly submitted stories over time, we showed that social filtering is an effective information filtering approach. Specifically, we showed that (a) users tend to like stories submitted by friends and (b) users tend to like stories their friends read and liked. Social filtering is a promising new technology that can be used to personalize and tailor information to individual users: for example, through personal front pages.

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عنوان ژورنال:
  • CoRR

دوره abs/cs/0612046  شماره 

صفحات  -

تاریخ انتشار 2007