  Despite the maturity already achieved by recommender systems algorithms,
little is known about how to obtain and provide users with a proper rationale
for a recommendation. Transparency and effectiveness of recommender systems may
be increased when explanations are provided. In particular, identifying of
helpful argumentative content from reviews can be leveraged to generate textual
explanations. In this paper, we investigate the reasons why a review might be
considered helpful, and show that the perception of credibility and
convincingness mediates the relationship between helpfulness and the perception
of objectivity and relevant aspects addressed. Our findings led us to suggest
an argumentbased approach to automatically extracting helpful content from
hotel reviews, a domain that differs from those that best fit classical
argumentation theories.
