What Makes an Explanation Good: A Systematic Review Examining Recommender System Explanations from User Perspective

Recommender systems play an important role in our digital lives, affecting our choices in areas such as e-commerce, music, movies, and news. As these systems become more complex, it is crucial to understand how and why items are recommended. Providing explanations in recommender systems can help users better understand these recommendations, which can increase trust, satisfaction, and engagement. However, it is challenging to design and present these explanations effectively so that users can easily understand them. Many studies have investigated user preferences on how to design explanations, but there is a lack of a comprehensive review that brings all these findings together. In this systematic review, we collected and analyzed many studies that explore how to design good explanations in recommender systems based on user opinions. Our review covers various fields to reflect different user experiences. The paper starts by defining key concepts related to explanations in recommender systems, different types of explanations, and research directions. The PRISMA methodology, which was used to review the last 10 years of research reporting user perceptions of the explanations of recommendation systems, is presented. The systematic review results in essential factors that should be considered when designing explanations, as they affect user satisfaction and understanding. Finally, future research directions are suggested to improve the explanation design in recommender systems.