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Rankings are the primary interface through which many online platforms match users to items (e.g.
Fair Learning-to-Rank from Implicit Feedback
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Recommendations as Treatments: Debiasing Learning and Evaluation. In ICML
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Controlling popularity bias in learning-to-rank recommendation. In ACM RecSys
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Fairness of Exposure in Rankings. In ACM SIGKDD
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The spread of true and false news online
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Beyond Personalization: Research Directions in Multistakeholder Recommendation
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TREC Fair Ranking Track
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Intervention Harvesting for Context-Dependent Examination-Bias Estimation. In SIGIR
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The few-get-richer: a surprising consequence of popularity-based rankings
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Policy Learning for Fairness in Ranking
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Consequential ranking algorithms and long-term welfare
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