Abstract:

Tourism is an important economic activity for many countries and the ability of understanding visitor needs as they evolve over time is a priority for all involved stakeholders. The analysis of textual reviews written by travelers on various online platforms may be a valuable tool in this direction. In this work, we showcase the potential of this idea by examining 8 well-known attractions in the City of Athens, Greece. After retrieving the relevant data from two popular online services, we employ a state-of-the-art transformer-based language model for two tasks; the extraction of distinctive keywords and phrases out of the free-text reviews and the assignment of a sentiment score to each review. Based on this information, we can associate certain keywords and phrases with specific sentiment values and monitor their evolution over time, in the context of specific touristic {&} cultural places. The analysis that follows explores the potential of this idea in more detail.