On the inaccuracy of numerical ratings: dealing with biased opinions in social networks

In this work, we study the potential problems emanating from using numerical ratings in social networks to rank entities regarding their reputation. In particular, we empirically demonstrate how reputation rankings as collected and managed by current systems are likely to be skewed due to subjectivity problems associated with the use of numerical ratings to encapsulate preferences. With the aim of overcoming these problems, we put forward an approach in which users are asked for their opinions about entities in a comparative fashion. In order to select the most appropriate users to be queried, we take advantage of the social structure derived from the interactions among users and entities following a principle of heterogeneity. Finally, we evaluate the proposed approach in the domain of movie ratings by using real datasets collected from different web sites.