The rise of digital libraries and the pertinent problem of information overload have contributed to the growing popularity of Scientific Recommender Systems (SRS). The frequent human recommender interactions and the impact of these systems on society raise issues of ethical concern. However, existing research on the ethics of SRS is limited in terms of its application to these systems. The challenge of providing “fair” recommendations and understanding what constitutes fairness in the domain of SRS is necessary to address. This study aims to conceptualize fairness in the chosen context and identify the antecedents to the perceived fairness of a system. Moreover, the study aims to investigate the impact of perceived fairness on trust in the system.
Yadav, Pratyush and Pervin, Nargis, "Antecedents of Perceived Fairness and User Trust in Scientific Recommender Systems" (2022). PACIS 2022 Proceedings. 89.
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