Social Choice and the Problem of Recommending Essential Readings

摘要

We tackle the practical problem of finding a good rule to recommend a collective set of news items to a group of media consumers with possibly very disparate individual interest in the available items. For our analysis, we adapt a formal framework from voting theory in Computational Social Choice to the media setting in order to compare the performance of five recommendation rules with respect to several desirable properties of recommendation sets. Through simulations, we find that polarization of the audience limits how well these rules can perform in general. On the other hand, greater diversity or universality can be achieved at only low cost in utility.