Ricardo Lage
Frederico Durao
ABSTRACT
In this paper we propose a group recommendation model that infers the group preferences based on the actions of its members. Such recommendations can be useful when individuals are working together in areas that require relevant up-to-date news information to support decisions. To test our model, we used Twitter, a microblogging service, as a platform to recommend links to news articles. To evaluate our model, we compared the group satisfaction with different strategies of group recommendation. Results show that our model obtained an average group rating of 3.58 out of 5 over the recommendations given to the group. This represents an improvement of approximately 25% over the best performing strategy we tested. We also analyzed the impact of different actions on Twitter and of a time decay parameter on group satisfaction
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