Transparency for Beyond-Accuracy Experiences: A Novel User Interface for Recommender Systems

Abstract

Facilitating serendipitous recommendations via a user interface for a recommender system is challenging. Recommender systems that facilitate serendipitous recommendations create what are considered to be beyond-accuracy experiences. Because serendipitous recommendations are unexpected, users may experience some trust issues with the recommender system. This paper reports on the use of transparency for connection-making (a process/stage of serendipitous experience) in serendipity recommendations generation and examines trust with respect to an interactive serendipitous recommender system. We developed a user interface for JabRef (related work tab). The experiment studied the responses of users, comprised of undergraduate students, in a university environment. Data was collected for both subjective and objective evaluations. The analysis was used to determine the significance and impact of transparency in recommender systems in which serendipitous recommendations are generated. The results showed that greater transparency has a positive impact on user experience, helps with connection-making, and enhances the trust of learners who use recommender systems for learning purposes. Such systems can be used by faculty members and students during research and supervision in order to facilitate finding new research topics and trust in such systems.