De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems
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arXiv
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912339943489536 |
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| author | Burke, Robin Adomavicius, Gediminas Bogers, Toine Di Noia, Tommaso Kowald, Dominik Neidhardt, Julia Özgöbek, Özlem Pera, Maria Soledad Tintarev, Nava Ziegler, Jürgen |
| author_facet | Burke, Robin Adomavicius, Gediminas Bogers, Toine Di Noia, Tommaso Kowald, Dominik Neidhardt, Julia Özgöbek, Özlem Pera, Maria Soledad Tintarev, Nava Ziegler, Jürgen |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05170 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems Burke, Robin Adomavicius, Gediminas Bogers, Toine Di Noia, Tommaso Kowald, Dominik Neidhardt, Julia Özgöbek, Özlem Pera, Maria Soledad Tintarev, Nava Ziegler, Jürgen Information Retrieval Machine Learning 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. |
| title | De-centering the (Traditional) User: Multistakeholder Evaluation of Recommender Systems |
| topic | Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2501.05170 |