Abstract
In today’s society, online reviews play a significant role in tourist’s decision making and understanding the emotions expressed in reviews can provide valuable insights into tourists’ perceptions. The study bears an understanding of emotions that tourists express in user generated content, aiming to gain insights into the satisfaction experienced within touristic activities. In contrast to traditional research, this study conceptualizes emotions not only in terms of positive, negative, or neutral sentiment, but builds on emotion theory which proposes primary emotions, such as joy, love, anger, or fear. The study successfully shows that primary emotions in online reviews can be detected using deep learning methods. Findings reveal the multi-faceted nature of emotional experiences within the scope of tourism and show the influence of certain emotions towards tourist satisfaction.