Exploring the Effects of Feed-Forward and Feedback on Information Disclosure and User Experience in a Context-Aware Recommender System
When disclosing information to a recommender system, users need to trade off its usefulness for receiving better recommendations with the privacy risks incurred through its disclosure. The paper describes a series of studies that will investigate the use of feed-forward and feedback messages to inform users about the potential usefulness of their disclosure. They hypothesize that this approach will influence the user experience in several interesting ways. Recommender systems for mobile applications need to provide immediate benefit to users, or else they may discontinue using them. Many recommender systems, however, give adequate recommendations after an extensive period of use only. Context-aware recommender systems use context data to overcome this new-user problem. Previous recommender systems have used location, system usage behavior, demographics, and implicit feedback.