Designing for the beter by taking users into account: A qalitative evaluation of user control mechanisms in (NEWS) recommender systems

J. Harambam, M. Makhortykh, D. Bountouridis, J. Van Hoboken

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

© 2019 Association for Computing Machinery.Recommender systems (RS) are on the rise in many domains. While they ofer great promises, they also raise concerns: lack of transparency, reduction of diversity, little to no user control. In this paper, we align with the normative turn in computer science which scrutinizes the ethical and societal implications of RS. We focus and elaborate on the concept of user control because that mitigates multiple problems at once. Taking the news industry as our domain, we conducted four focus groups, or moderated think-aloud sessions, with Dutch news readers (N=21) to systematically study how people evaluate diferent control mechanisms (at the input, process, and output phase) in a News Recommender Prototype (NRP). While these mechanisms are sometimes met with distrust about the actual control they ofer, we found that an intelligible user profle (including reading history and fexible preferences settings), coupled with possibilities to infuence the recommendation algorithms is highly valued, especially when these control mechanisms can be operated in relation to achieving personal goals. By bringing (future) users' perspectives to the fore, this paper contributes to a richer understanding of why and how to design for user control in recommender systems.
Original languageEnglish
Title of host publicationRecSys 2019 - 13th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages69-77
ISBN (Electronic)9781450362436
DOIs
Publication statusPublished - 10 Sept 2019
Externally publishedYes
Event13th ACM Conference on Recommender Systems, RecSys 2019 - Copenhagen, Denmark
Duration: 16 Sept 201920 Sept 2019

Conference

Conference13th ACM Conference on Recommender Systems, RecSys 2019
Country/TerritoryDenmark
CityCopenhagen
Period16/09/1920/09/19

Funding

This study is part of the Fair News project, which is fnanced by the Netherlands Organisation for Scientifc Research (NWO) as part of the recently created National Research Agenda in the Netherlands. Project number: 400.17.605. Cooperating partner of this project is De Persgroep Nederland BV, with whom we productively collaborated

FundersFunder number
De Persgroep Nederland BV
Nederlandse Organisatie voor Wetenschappelijk Onderzoek400.17.605

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