2021-02-02
Pitch proposal: Recommenders with a mission - assessing diversity in news recommendations
Publication
Publication
By helping the user find relevant and important online content, news recommenders have the potential to fulfill a crucial role in a democratic society. Simultaneously, recent concerns about filter bubbles, fake news and selective exposure are symptomatic of the disruptive potential of these digital news recommenders. Recommender systems can make or break filter bubbles, and as such can be instrumental in creating either a more closed or a more open internet. This document details a pitch for an ongoing project that aims to bridge the gap between normative notions of diversity, rooted in democratic theory, and quantitative metrics necessary for evaluating the recommender system. Our aim is to get feedback on a set of proposed metrics grounded in social science interpretations of diversity
| Additional Metadata | |
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| doi.org/10.1007/978-3-030-65965-3_38 | |
| Communications in Computer and Information Science | |
| Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), 2020 | |
| creativecommons.org/licenses/by/4.0/ | |
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Vrijenhoek, S.& Helberger, N. (2021). Pitch proposal: Recommenders with a mission - assessing diversity in news recommendations. ECML PKDD: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 554–561.https://doi.org/10.1007/978-3-030-65965-3_38 |
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