#26: Diversity in Recommender Systems with Sanne Vrijenhoek

Recsperts - Recommender Systems Experts

In episode 26 of Recsperts, I speak with Sanne Vrijenhoek, a PhD candidate at the University of Amsterdam’s Institute for Information Law and the AI, Media & Democracy Lab. Sanne’s research explores diversity in recommender systems, particularly in the news domain, and its connection to democratic values and goals.

We dive into four of her papers, which focus on how diversity is conceptualized in news recommender systems. Sanne introduces us to five rank-aware divergence metrics for measuring normative diversity and explains why diversity evaluation shouldn’t be approached blindly—first, we need to clarify the underlying values. She also presents a normative framework for these metrics, linking them to different democratic theory perspectives. Beyond evaluation, we discuss how to optimize diversity in recommender systems and reflect on missed opportunities—such as the RecSys Challenge 2024, which could have gone beyond accuracy-chasing. Sanne also shares her recommendations for improving the challenge by incorporating objectives such as diversity.

During our conversation, Sanne shares insights on effectively communicating recommender systems research to non-technical audiences. To wrap up, we explore ideas for fostering a more diverse RecSys research community, integrating perspectives from multiple disciplines.

Enjoy this enriching episode of RECSPERTS - Recommender Systems Experts.
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• (00:00) - Introduction
• (03:24) - About Sanne Vrijenhoek
• (14:49) - What Does Diversity in RecSys Mean?
• (26:32) - Assessing Diversity in News Recommendations
• (34:54) - Rank-Aware Divergence Metrics to Measure Normative Diversity
• (01:01:37) - RecSys Challenge 2024 - Recommendations for the Recommenders
• (01:11:23) - RecSys Workshops - NORMalize and AltRecSys
• (01:15:39) - On the Different Conceptualizations of Diversity in RecSys
• (01:28:38) - Closing Remarks

Links from the Episode:

• Sanne Vrijenhoek on LinkedIn
• Informfully
• MIND: MIcrosoft News Dataset
• RecSys Challenge 2024
• NORMalize 2023: The First Workshop on the Normative Design and Evaluation of Recommender Systems
• NORMalize 2024: The Second Workshop on the Normative Design and Evaluation of Recommender Systems
• AltRecSys 2024: The AltRecSys Workshop on Alternative, Unexpected, and Critical Ideas in Recommendation

Papers:

• Vrijenhoek et al. (2021): Recommenders with a Mission: Assessing Diversity in News Recommendations
• Vrijenhoek et al. (2022): RADio – Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
• Heitz et al. (2024): Recommendations for the Recommenders: Reflections on Prioritizing Diversity in the RecSys Challenge
• Vrijenhoek et al. (2024): Diversity of What? On the Different Conceptualizations of Diversity in Recommender Systems
• Helberger (2019): On the Democratic Role of News Recommenders
• Steck (2018): Calibrated Recommendations

General Links:

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• Send me your comments, questions and suggestions to [email protected]
• Recsperts Website