Abstract
Consumer-generated reviews (CGR) entail a significant potential business volume in terms of translation and post-editing, however travel review platforms usually rely solely on raw machine translation. As a new digital genre, CGR require specific post-editing guidelines, therefore, this paper focuses on the analysis of a corpus of Spanish machine translation output of hotel reviews in order to identify error patterns and their effects on quality with the aim of designing a post-editing strategy adapted to this particular type of text.
