Comparing fair ranking metrics. Raj, A., Wood, C., Montoly, A., & Ekstrand, M. D In September, 2020. ![Comparing fair ranking metrics [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex Ranking is a fundamental aspect of recommender systems. However, ranked outputs can be susceptible to various biases; some of these may cause disadvantages to members of protected groups. Several metrics have been proposed to quantify the (un)fairness of rankings, but there has not been to date any direct comparison of these metrics. This complicates deciding what fairness metrics are applicable for specific scenarios, and assessing the extent to which metrics agree or disagree. In this paper, we describe several fair ranking metrics in a common notation, enabling direct comparison of their approaches and assumptions, and empirically compare them on the same experimental setup and data set. Our work provides a direct comparative analysis identifying similarities and differences of fair ranking metrics selected for our work.
@inproceedings{raj_comparing_2020,
title = {Comparing fair ranking metrics},
url = {http://arxiv.org/abs/2009.01311},
abstract = {Ranking is a fundamental aspect of recommender systems. However, ranked
outputs can be susceptible to various biases; some of these may cause
disadvantages to members of protected groups. Several metrics have been
proposed to quantify the (un)fairness of rankings, but there has not been
to date any direct comparison of these metrics. This complicates deciding
what fairness metrics are applicable for specific scenarios, and assessing
the extent to which metrics agree or disagree. In this paper, we describe
several fair ranking metrics in a common notation, enabling direct
comparison of their approaches and assumptions, and empirically compare
them on the same experimental setup and data set. Our work provides a
direct comparative analysis identifying similarities and differences of
fair ranking metrics selected for our work.},
author = {Raj, Amifa and Wood, Connor and Montoly, Ananda and Ekstrand, Michael D},
month = sep,
year = {2020},
}
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