Following the idiom “A picture is worth a thousand words”, recent tourism and hospitality research has adopted deep learning techniques to better understand the content and effect of photographs. This exploratory study delves into image content, to learn which sets of images relate to positive and negative reviews. Several image classes appear in both positive and negative reviews. However, the distribution of images across classes differs. Of interest were images that did not represent core hotel services, which suggests that users review the surrounding area, attractions, and activities as well as the hotel property. This finding is relevant for managers to learn which areas (to engage with) could improve guest experiences.

Key words: online hotel reviews, image classification, image