{"ID":2853234,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.16972","arxiv_id":"2510.16972","title":"Preference Measurement Error, Concentration in Recommendation Systems, and Persuasion","abstract":"Algorithmic recommendation based on noisy preference measurement is prevalent in recommendation systems. This paper discusses the consequences of such recommendation on market concentration and inequality. Binary types denoting a statistical majority and minority are noisily revealed through a statistical experiment. The achievable utilities and recommendation shares for the two groups can be analyzed as a Bayesian Persuasion problem. While under arbitrary noise structures, effects on concentration compared to a full-information market are ambiguous, under symmetric noise, concentration increases and consumer welfare becomes more unequal. We define symmetric statistical experiments and analyze persuasion under a restriction to such experiments, which may be of independent interest.","short_abstract":"Algorithmic recommendation based on noisy preference measurement is prevalent in recommendation systems. This paper discusses the consequences of such recommendation on market concentration and inequality. Binary types denoting a statistical majority and minority are noisily revealed through a statistical experiment. T...","url_abs":"https://arxiv.org/abs/2510.16972","url_pdf":"https://arxiv.org/pdf/2510.16972v1","authors":"[\"Andreas Haupt\"]","published":"2025-10-19T19:19:12Z","proceeding":"econ.TH","tasks":"[\"econ.TH\",\"cs.CY\"]","methods":"[]","has_code":false}