Incentives for Item Duplication under Fair Ranking Policies
Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello and, Gian Antonio Susto

TL;DR
This paper investigates how fair ranking policies can incentivize item duplication, leading to increased redundancy and potential fairness issues, especially in systems where duplicates gain extra exposure.
Contribution
It is the first study to analyze the impact of fair ranking policies on incentivizing item duplication and its implications for fairness and diversity.
Findings
Fair ranking policies may incentivize duplication due to exposure benefits.
Duplicates can gain significantly more exposure under fairness-aware policies.
Incentivizing duplication conflicts with diversity and fairness objectives.
Abstract
Ranking is a fundamental operation in information access systems, to filter information and direct user attention towards items deemed most relevant to them. Due to position bias, items of similar relevance may receive significantly different exposure, raising fairness concerns for item providers and motivating recent research into fair ranking. While the area has progressed dramatically over recent years, no study to date has investigated the potential problem posed by duplicated items. Duplicates and near-duplicates are common in several domains, including marketplaces and document collections available to search engines. In this work, we study the behaviour of different fair ranking policies in the presence of duplicates, quantifying the extra-exposure gained by redundant items. We find that fairness-aware ranking policies may conflict with diversity, due to their potential to…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Auction Theory and Applications · Game Theory and Voting Systems
