The social approach in recommender systems relies on the hypothesis that users' preferences are coherent between users. Although it provides high quality recommendations, some users never get any high quality recommendations. We think these users have preferences different from others and we propose measures to identify them. The experiments conducted show that they improve the identification of these users, in comparison with the literature.