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Deliberative Diversity for News Recommendations: Operationalization and Experimental User Study

Heitz, Lucien; Lischka, Juliane A; Abdullah, Rana; Laugwitz, Laura; Meyer, Hendrik; Bernstein, Abraham (2023). Deliberative Diversity for News Recommendations: Operationalization and Experimental User Study. In: RecSys '23: Seventeenth ACM Conference on Recommender Systems, Singapore Singapore, 18 September 2023 - 22 September 2023. ACM Digital library, 813-819.

Abstract

News recommender systems are an increasingly popular field of study that attracts a growing interdisciplinary research community. As these systems play an essential role in our daily lives, the mechanisms behind their curation processes are under scrutiny. In the area of personalized news, many platforms make design choices driven by economic incentives. In contrast to such systems that optimize for financial gain, there can be norm-driven diversity systems that prioritize normative and democratic goals. However, their impact on users in terms of inducing behavioral change or influencing knowledge is still understudied. In this paper, we contribute to the field of news recommender system design by conducting a user study that examines the impact of these normative approaches. We a.) operationalize the notion of a deliberative public sphere for news recommendations, show b.) the impact on news usage, and c.) the influence on political knowledge, attitudes and voting behavior. We find that exposure to small parties is associated with an increase in knowledge about their candidates and that intensive news consumption about a party can change the direction of attitudes of readers towards the issues of the party.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Physical Sciences > Information Systems
Physical Sciences > Software
Physical Sciences > Control and Systems Engineering
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:22 September 2023
Deposited On:12 Feb 2024 11:32
Last Modified:21 Oct 2024 17:10
Publisher:ACM Digital library
Series Name:Proceedings of the ACM Conference on Recommender Systems
ISBN:979-8-4007-0241-9
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1145/3604915.3608834
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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