Evaluating User's Personality and Social Interactions for Groups Recommendations

Common approaches to provide group recommendations are based on the aggregation of the recommendations that are provided, for each group’s member, by an individual recommendation system, using social choice functions. These techniques do not consider factor like social interactions, roles, influences, and group members’ personality that model real group’s decision-making process. Recent approaches tried to include these factors by introducing social-based weights in the aggregation of preferences or social aware utility functions. On the basis of these evaluations we propose two possible approaches, one based on the study of user’s personality, in particular, on the agreeableness factor, and a second one based on the analysis of social interaction between group’s members on a social network, to determine a dominance factor for each user in the group. The conducted pilot studies show that these approaches can increase the goodness of the recommendation provided and the satisfaction of group’s members with respect to standard aggregation mechanisms.