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

Abstract

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 practitioners at three different public service media organizations in the Netherlands conceptualize diversity within the scope of their recommender systems. We provide an overview of the goals that they have with diversity in their systems, which aspects are relevant, and how recommendations should be diversified. We show that even within this limited domain, conceptualization of diversity greatly varies, and argue that it is unlikely that a standardized conceptualization will be achieved. Instead, we should focus on effective communication of what diversity in this particular system means, thus allowing for operationalizations of diversity that are capable of expressing the nuances and requirements of that particular domain.

References in corpus (5)

• Stance Detection on Social Media: State of the Art and Trends
• The Forgotten Margins of AI Ethics
• Diversity and Inclusion Metrics in Subset Selection
• Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently?
• Much Ado About Gender: Current Practices and Future Recommendations for Appropriate Gender-Aware Information Access

Cited by in corpus (4)

• D-RDW: Diversity-Driven Random Walks for News Recommender Systems
• Algorithms in the Stacks: Investigating automated, for-profit diversity audits in public libraries
• Informfully Recommenders -- Reproducibility Framework for Diversity-aware Intra-session Recommendations
• Modeling Musical Genre Trajectories through Pathlet Learning