Abstract:Recommender systems -and especially matrix factorization-based collaborative filtering algorithms -play a crucial role in mediating our access to online information. We show that such algorithms induce a particular kind of stereotyping: if preferences for a set of items are anticorrelated in the general user population, then those items may not be recommended together to a user, regardless of that user's preferences and ratings history. First, we introduce a notion of joint accessibility, which measures the ex… Show more
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