Using Multiwinner Voting to Search for Movies

Abstract

We show a prototype of a system that uses multiwinner voting to suggest resources (e.g., movies) related to a given query. For example, a user provides a movie and the system answers with a list of movies that, depending on the voting rule used, are either very closely or more loosely related to the input one. This gives a way of controlling the diversity of the results (and an ability to escape one’s filter bubble). We test our system both on synthetic data and on the MovieLens dataset.