Quantifying the Impact of User Attentionon Fair Group Representation in Ranked Lists
Companion Proceedings of The 2019 World Wide Web Conference, pp. 553-562, 2019.
In this work, we introduce a novel metric for auditing group fairness in ranked lists. Our approach offers two benefits compared to the state of the art. First, we offer a blueprint for modeling of user attention. Rather than assuming a logarithmic loss in importance as a function of the rank, we can account for varying user behaviors thr...More
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