Physical Sciences and Mathematics Commons^™

Explaining Social Recommendations To Casual Users: Design Principles And Opportunities, Chun-Hua Tsai, Peter Brusilovsky

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Recommender systems have become popular in recent years, and ordinary users are more likely to rely on such service when completing various daily tasks. The need to design and build explainable recommender interfaces is increasing rapidly. Most of the designs of such explanations are intended to reflect the underlying algorithms by which the recommendations are computed. These approaches have been shown to be useful for obtaining system transparency and trust. However, little is known about how to design explanation interfaces for causal (non-expert) users to achieve different explanatory goals. As a first step toward understanding the user interface design factors, …