Inproceedings,
Dynamics of collaborative document rating systems
WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis, page 46--55. New York, NY, USA, ACM, (2007)
DOI: http://doi.acm.org/10.1145/1348549.1348555
Abstract
The rise of social media sites, such as blogs, wikis, Digg and Flickr among others, underscores a transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. The social news aggregator Digg allows users to submit links to and vote on news stories. Like other social media sites, Digg also allows users to designate others as "friends" and easily track friends' activities: what new stories they submitted, commented on or liked. 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. We construct a mathematical model to study how collaborative rating and promotion of news stories emerges from independent decisions made by many users. The model takes into account user behavior: e.g., whether they read stories on the front page or through the Friends interface. Solutions of the model qualitatively reproduce the observed dynamics of votes received by actual stories on Digg.
