#3200. Exploring folk theories of algorithmic news curation for explainable design

October 2026publication date
Proposal available till 12-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Social Sciences (all);
Arts and Humanities (miscellaneous);
Developmental and Educational Psychology;
Human-Computer Interaction;
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Abstract:
Algorithmic news curation determines users’ news exposure in the online environment. To combat this, explainable algorithmic news curation systems are necessary. One user-centered solution to design these systems can be achieved through the systematic exploration of user folk theories. The research conducted twelve in-depth semi-structured interviews to explore the user preferences for explainable system design, and folk theories of algorithmic news curation. The scholars found a psychological trade-off between the desire for transparency and feelings of creepiness, thus a preference for explanations to be hidden. The results are compared to previous folk theories and discussed in terms of the ‘sweet spot’ of system transparency. Folk theories is a key requirement for designing explainable algorithmic news curation systems.
Keywords:
algorithmic decision-making; explanation; folk theory; news curation; qualitative research; user interface

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