SpART: Spotlight on Artists in Recommender Systems

1 September 2019
Photo by Image by Monsterkoi from Pixabay

The purpose of this project is to understand how current systems used to recommend music affect artists and to propose alternative solutions that could benefit the artists. The goal is to identify potential problems that affect artists, and to draw on the artists’ perspective about how future recommender systems could work.

music recommender systems artists fairness algorithmic decision-making recommender systems

Posts

Karlijn Dinnissen has successfully passed her first-year assessment
Today, Karlijn Dinnissen had the first-year assessment of her PhD, which she—as expected—successfully passed.
9 February 2023 1 min read news
Project
Karlijn Dinnissen has successfully passed her first-year assessment

Publications

How control and transparency for users could improve artist fairness in music recommender systems
As streaming services have become a main channel for music consumption, they significantly impact various stakeholders: users, artists …
Karlijn Dinnissen, Christine Bauer
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How control and transparency for users could improve artist fairness in music recommender systems
Strategies for mitigating artist gender bias in music recommendation: a simulation study
Recommender systems are prone to various biases. Hence, bias mitigation approaches are needed to counteract those. In the music sector, …
Christine Bauer, Andrés Ferraro
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Amplifying artists' voices: item provider perspectives on influence and fairness of music streaming platforms
The majority of music consumption nowadays takes place on music streaming platforms. Whichever artists, albums, or songs are exposed to …
Karlijn Dinnissen, Christine Bauer
PDF Cite Project DOI ACM Author-izer DOI CORE 2023: B GGS 2021: B nominated for Best Student Paper Award
Fairness in music recommender systems: a stakeholder-centered mini review
The performance of recommender systems highly impacts both music streaming platform users and the artists providing music. As fairness …
Karlijn Dinnissen, Christine Bauer
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What is fair? Exploring the artists' perspective on the fairness of music streaming platforms
Music streaming platforms are currently among the main sources of music consumption, and the embedded recommender systems significantly …
Andrés Ferraro, Xavier Serra, Christine Bauer
PDF Cite Project DOI Postprint DOI CORE 2023: B GGS 2021: B
Break the loop: gender imbalance in music recommenders
As recommender systems play an important role in everyday life, there is an increasing pressure that such systems are fair. Besides …
Andrés Ferraro, Xavier Serra, Christine Bauer
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Report on the ISMIR 2020 special session: How do we help artists?
The 21st edition of the Annual Conference of the International Society for Music Information Retrieval (ISMIR) introduced so-called …
Christine Bauer
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Allowing for equal opportunities for artists in music recommendation
Promoting diversity in the music sector is widely discussed on the media. While the major problem may lie deep in our society, music …
Christine Bauer
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Music recommender systems: challenges and opportunities for non-superstar artists
Music Recommender Systems (MRS) are important drivers in music industry and are widely adopted by music platforms. Other than most MRS …
Christine Bauer, Marta Kholodylo, Christine Strauss
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