activity
20202025
most citedBuilding Human Values into Recommender Systems: An Interdisciplinary Synthesis

107 citations · 129 across the 7 of their papers we have counts for

collaborators

8 papers

cs.IR2025★ 1 cited

How public datasets constrain the development of diversity-aware news recommender systems, and what law could do about it

Max van Drunen, Sanne Vrijenhoek

News recommender systems increasingly determine what news individuals see online. Over the past decade, researchers have extensively critiqued recommender systems that prioritise n…

cs.IR2024★ 13 cited

Diversity of What? On the Different Conceptualizations of Diversity in Recommender Systems

Sanne Vrijenhoek, Savvina Daniil, Jorden Sandel +1

Diversity is a commonly known principle in the design of recommender systems, but also ambiguous in its conceptualization. Through semi-structured interviews we explore how practit…

cs.CL2023

Improving and Evaluating the Detection of Fragmentation in News Recommendations with the Clustering of News Story Chains

Alessandra Polimeno, Myrthe Reuver, Sanne Vrijenhoek +1

News recommender systems play an increasingly influential role in shaping information access within democratic societies. However, tailoring recommendations to users' specific inte…

cs.IR2023

Do you MIND? Reflections on the MIND dataset for research on diversity in news recommendations

Sanne Vrijenhoek

The MIND dataset is at the moment of writing the most extensive dataset available for the research and development of news recommender systems. This work analyzes the suitability o…

cs.IR2022

RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations

Sanne Vrijenhoek, Gabriel Bénédict, Mateo Gutierrez Granada +2

In traditional recommender system literature, diversity is often seen as the opposite of similarity, and typically defined as the distance between identified topics, categories or…

cs.IR2022★ 107 cited

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Jonathan Stray, Alon Halevy, Parisa Assar +18

Recommender systems are the algorithms which select, filter, and personalize content across many of the worlds largest platforms and apps. As such, their positive and negative effe…