Using readability tests to predict helpful product reviews

User-generated content provides online consumers with a wealth of information. Given the ever-increasing quantity of available content and the lack of quality control applied to this content, there is a clear need to enhance the user experience when it comes to effectively leveraging this vast information source. In this paper, we address these issues in the context of user-generated product reviews. We expand
on recent work to consider the performance of structural and readability feature sets on the classification of helpful product reviews. Our findings, based on a large-scale evaluation of TripAdvisor and Amazon reviews, indicate that structural and readability features are useful predictors for Amazon product reviews but less so for TripAdvisor hotel reviews.