Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness

TL;DR

This paper explores the relationship between multi-stakeholder recommendation systems and multi-sided fairness, providing a taxonomy of system classes and discussing fairness considerations in such contexts.

Contribution

It introduces a taxonomy of multi-stakeholder recommender systems and highlights the connection between fairness concerns and multi-stakeholder recommendation.

Findings

Defines common classes of multi-stakeholder recommender systems

Discusses how fairness concerns influence system design

Highlights the importance of fairness in multi-stakeholder settings

Abstract

There is growing research interest in recommendation as a multi-stakeholder problem, one where the interests of multiple parties should be taken into account. This category subsumes some existing well-established areas of recommendation research including reciprocal and group recommendation, but a detailed taxonomy of different classes of multi-stakeholder recommender systems is still lacking. Fairness-aware recommendation has also grown as a research area, but its close connection with multi-stakeholder recommendation is not always recognized. In this paper, we define the most commonly observed classes of multi-stakeholder recommender systems and discuss how different fairness concerns may come into play in such systems.