Votes and Comments in Recommender Systems: The Case of Digg
نویسنده
چکیده
In this paper we describe Digg, a successful social news aggregator web site. Digg allows users to submit links to news stories, as well as vote and comment on other submitted stories. It also enables users to designate other users as friends and makes it easy to track their activities, thereby creating a social network within Digg. We perform a statistical analysis of a sample of 1000 popular stories on Digg. We explore relationships and correlations between the two main ways of interacting with submissions on the website and we explain that votes (diggs) and comments constitute qualitatively different mechanisms for providing recommendations. Furthermore, we investigate the voting and commenting behavior for different content categories and discover significant differences among them. Author
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