GroupFun: Group recommender systems as a voting problem


Aggregating users’ individual preference and recommending a common set of items for a group has become a challenging topic in group recommender systems and social websites. This issue is mainly concerned with the following three objectives: eliciting individual users’ preferences, suggesting outcomes that maximize the overall satisfaction for all users and ensuring that the aggregation mechanism is resistant to individual users’ manipulation. Firstly we show how our proposed probabilistic weighted-sum algorithm (PWS) works and emphasize on its advantages. Then we compare PWS with related approaches implemented in similar systems using the case of our music recommender, GroupFun. We describe an experiment design to study users’ perceptions of the algorithms, their perceived fairness and incentives to manipulate the final recommendation outcome. We expect our results to show that PWS will be perceived as fair and diversity- and discovery-driven, thus enhancing the group’s satisfaction. Our future work will focus on the actual evaluation of GroupFun using the experiment design presented here.


Voting, Recommender systems, Group decision making, Social choice, Social websites, Dynamic selection, Preference aggregation, User incentives, Game Theory, Music preference, online user decision and behavior, social websites


2010 – 2012


George Popescu and Pearl Pu


Swiss National Science Foundation


  • George Popescu and Pearl Pu. What’s the Best Music You Have? Designing Music Recommendation for Group Enjoyment in GroupFun. In Works-in-Progress of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI ’12), Austin, TX, USA, May 05-10, 2012.
  • George Popescu and Pearl Pu. Probabilistic Game Theoretic Algorithms for Group Recommender Systems. In Procedding of the Workshop on Workshop on Music Recommendation and Discovery (WOMRAD’11), in conjunction with the 5th ACM Conference on Recommender Systems (RecSys’11), Chicago, USA, Oct. 23 – 27, 2011.
  • George Popescu and Pearl Pu. Eye-tracking Group Influence – Experiment Design and Results. EPFL Technical Report. Lausanne, VD, Switzerland, September 26, 2012.