Using readability tests to predict helpful product reviews


Paper presented at RIAO 2010 the 9th international conference on Adaptivity, Personalization and Fusion of Heterogeneous Information, Paris, France, April 28-30, 2010User-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.Not applicableURL of conference programme:〈=e

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This paper was published in Research Repository UCD.

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