Author ORCID Identifier
Document Type
Article
Publication Date
3-2018
Abstract
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, we conducted an international (across 13 countries) online survey of 14 active users of a social recommender system. This study captures user feedback in the field and frames it in terms of design principles and opportunities.
Recommended Citation
Tsai, C. H. & Brusilovsky, P. (2018). Explaining social recommendations to casual users: Design principles and opportunities. In Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion (IUI’18) (pp. 1-2). https://doi.org/10.1145/3180308.3180368
Comments
This was presented at In Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
DOI: https://doi.org/10.1145/3180308.3180368
IUI’18 Companion March 7–11, 2018, Tokyo, Japan © 2018 Copyright held by the owner/author(s).