Exposure diversity as a design principle for recommender systems
By Natali Helberger, Kari Karppinen, Lucia D'Acunto. 2018
312 citations recorded by the source corpus.
ABSTRACT Personalized recommendations in search engines, social media and also in more traditional media increasingly raise concerns over potentially negative consequences for diversity and the quality of public discourse. The algorithmic filtering and adaption of online content to personal preferences and interests is often associated with a decrease in the diversity of information to which users are exposed. Notwithstanding the question of whether these claims are correct or not, this article discusses whether and how recommendations can also be designed to stimulate more diverse exposure to information and to break potential ‘filter bubbles’ rather than create them. Combining insights from democratic theory, computer science and law, the article makes suggestions for design principles and explores the potential and possible limits of ‘diversity sensitive design’.
Subfields: Communication, Political Science and International Relations, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/899fa2e3176455118a0589e24338c15f4e6fc33b
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Citations in the corpus
- Do not blame it on the algorithm: an empirical assessment of multiple recommender systems and their impact on content diversity (2018, unknown): “So far, diversity is mainly discussed and measured in terms of political leaning of news sources and stories (e.g. Flaxman & Rao, 2016), thereby neglecting that diversity is a multi-dimensional concept that also encompasses topic plurality, genre, or the plurality in tone (Helberger et al., 2018).”
- Recommender systems and their ethical challenges (2020, background): “…by several authors is that news recommendation systems, in particular, must reach a trade-off between the expected relevance to the user and diversity when generating personalised recommendations based on pre-specified user preferences or behavioural data (Helberger et al. 2016; Reviglio 2017).”