A Picture is Worth a Thousand Words: Improving Usability and Robustness of Online Recommendation Systems
Tiffany Hyun‐Jin Kim, Virgil D. Gligor, Adrian Perrig · 2011
Recent statistics show that the number of online shoppers are increasing where the majority of them use online recommendation systems for product/service reviews. Although online reviews are becoming increasingly important, consumers face two major challenges of usability and robustness when they make purchase decisions based on the available reviews. More specifically, usability issues arise when consumers need to be able to extract relevant information given a high volume of data with uncertainty due to high variance. For robustness, judging the degree of truthfulness of the available recommendations can be a daunting task for consumers. In this paper, we propose a post-purchase tracking system as an enhancement to current online recommendation systems by embracing a peer review process and ask each consumer to score the reviews that previous consumers have posted. Furthermore, we propose to visualize the peer review processes such that people find the recommendation systems more efficient and useful to learn information. Our preliminary user study results indicate that our post-purchase tracking system is a promising approach that can help online consumers determine what information to trust with high confidence.