推荐系统需兼顾多方利益，而非仅关注用户满意度。
De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems
- 提出多利益相关方评估框架，涵盖提供者与消费者等多元主体。
- 强调评估需匹配各主体目标与价值，避免单一指标主导。
- 适合关注公平性、可持续性的推荐系统研究者与开发者。
多利益相关方推荐系统需考虑多个群体（包括但不限于内容提供者和消费者）的影响与偏好，而不仅聚焦于接收推荐的终端用户。由于其复杂性，这类系统无法像主流应用那样仅以单一主体的整体效用进行评价。本文探讨多利益相关方推荐系统评估的挑战，涵盖利益相关方范围、各主体的价值与具体目标，并讨论如何将理论原则转化为实际应用，提供具体案例。最后，展望该领域未来的研究方向，旨在为研究人员和从业者在设计、开发及研究具有多利益相关方特征的应用时，提供整合复杂且依赖领域的评估问题的指导。
原文摘要 · Abstract (English)
Multistakeholder recommender systems are those that account for the impacts and preferences of multiple groups of individuals, not just the end users receiving recommendations. Due to their complexity, these systems cannot be evaluated strictly by the overall utility of a single stakeholder, as is often the case of more mainstream recommender system applications. In this article, we focus our discussion on the challenges of multistakeholder evaluation of recommender systems. We bring attention to the different aspects involved -- from the range of stakeholders involved (including but not limited to providers and consumers) to the values and specific goals of each relevant stakeholder. We discuss how to move from theoretical principles to practical implementation, providing specific use case examples. Finally, we outline open research directions for the RecSys community to explore. We aim to provide guidance to researchers and practitioners about incorporating these complex and domain-dependent issues of evaluation in the course of designing, developing, and researching applications with multistakeholder aspects.
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