Following Trendsetters: Collective Decisions in Online Social Networks
Hawaii International Conference on System Sciences, January 2012
10 Pages Posted: 22 Sep 2012
Date Written: January 4, 2012
The convenience of sharing information online led to a tremendous amount of information available to Web users. The present work examines how people process information in online social networks, using Digg as an example. In Digg, users submit and vote for news stories they like, and the collective decisions of the users determine which news stories become prominent. How do Digg users scan the sea of submissions for stories they like? The results from the statistical analyses and computer simulations of Digg users’ voting behavior reveal that users filter out stories using the choices of trendsetters, rather than using the majority decisions. Stories that trendsetters like attract many followers and gain vast popularity.
Keywords: Collective decisions, trendsetters, followers, social network analysis, online communities
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