Towards Optimizing Ranking in Grid-Layout for Provider-side Fairness

ECIR24-g
2024

Amifa Raj and Michael D. Ekstrand. 2024. Towards Optimizing Ranking in Grid-Layout for Provider-side Fairness. To appear in Proceedings of the 46th European Conference on Information Retrieval (ECIR '24, IR for Good track). Proc. ECIR '24 (IR for Good track). Acceptance rate: 40.6%.

This paper was led by my Ph.D student Amifa Raj.

A laptop showing a streaming service with a grid of search results.
Photo by Tech Daily on Unsplash

Abstract

Information access systems, such as search engines and recommender systems, order and position results based on their estimated relevance. These results are then evaluated for a range of concerns, including provider-side fairness: whether exposure to users is fairly distributed among items and the people who created them. Several fairness-aware ranking and re-ranking techniques have been proposed to ensure fair exposure for providers, but this work focuses almost exclusively on linear layouts in which items are displayed in single ranked list. Many widely-used systems use other layouts, such as the grid views common in streaming platforms, image search, and other applications. Providing fair exposure to providers in such layouts is not well-studied. We seek to fill this gap by providing a grid-aware re-ranking algorithm to optimize layouts for provider-side fairness by adapting existing re-ranking techniques to grid-aware browsing models, and an analysis of the effect of grid-specific factors such as device size on the resulting fairness optimization. Our work provides a starting point and identifies open gaps in ensuring provider-side fairness in grid-based layouts.

Listed Under