Abstract
Recommender Systems (RS) help users to orientate themselves in large product assortments and provide decision support. Explanations help recommender systems to enhance their impact on users by, for instance, justifying made recommendations. Arguments provide reason in a more structured way, by denoting a conclusion that follows from one or more premises. While expert systems' explanation have a long tradition in using argumentative patterns, argumentative explanations for recommendations have not yet been systematically researched. This paper compares therefore the persuasion potential of different explanation styles (sentences, facts or argument style) by comparing the robustness of subjects' preferences when employing an additive utility model from conjoint analysis.