Selecting Trustworthy Partners by the Means of Untrustworthy Recommenders in Digitally Empowered Societies

摘要

In this work, we want to show that the introduction of categories can strongly improve the performance of recommendation, within the new digitally infrastructured societies. We state that, inside these highly dynamic contexts, in which more and more people are connected to each other but a substantial part of the communication happens between strangers, it is fundamental to restructure the concept of recommendation. We strongly believe that a good solution for many situations would be to combine inferential processes with recommendations, i.e. focusing on recommending categories of agents rather than specific individuals. Specifically, in this work we prove that category's recommendations are more robust to untrustworthy recommenders than individual recommendation. We tested our idea by the mean of a multi-agent social simulation. The results we obtained arc in agreement with our hypotheses and can be of important interest for the development of this sector.