  In this paper, we propose a novel approach for aggregating online reviews,
according to the opinions they express. Our methodology is unsupervised - due
to the fact that it does not rely on pre-labeled reviews - and it is agnostic -
since it does not make any assumption about the domain or the language of the
review content. We measure the adherence of a review content to the domain
terminology extracted from a review set. First, we demonstrate the
informativeness of the adherence metric with respect to the score associated
with a review. Then, we exploit the metric values to group reviews, according
to the opinions they express. Our experimental campaign has been carried out on
two large datasets collected from Booking and Amazon, respectively.
