Abstract

In recent years, recommender systems have started to exploit user-generated content, in particular online reviews, as an additional means of personalizing and explaining their predictions. However, reviews that are poorly written or perceived as fake may have a detrimental effect on the users' in the recommendations. Embedding so-called trust cues in the user interface is a technique that can help users judge the trustworthiness of presented information. We report preliminary results from an online user study that investigated the impact of cues---in the form of helpfulness votes---on the trustworthiness of online reviews for recommendations.

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