A Sentiment Analysis Model Based on User Experiences of Dubrovnik on the Tripadvisor Platform

Abstract

Emerging research indicates that sentiment analyses of Dubrovnik focus mainly on hotel accommodations and restaurants. However, little attention has been paid to attractions, even though they are an important aspect of destinations and require more care and investment than amenities. This study examines how visitors experience Dubrovnik based on the reviews published on the Tripadvisor platform. Data were collected by implementing a web-scraping script to retrieve reviews of the tourist attraction “Old Town” from Tripadvisor, while data augmentation and random oversampling techniques were applied to address class imbalances. A sentiment analysis model, based on the pre-trained RoBERTa, was also developed and evaluated. In particular, a sentiment analysis was performed to compare reviews from 2022 and 2023. Overall, the results of this study are promising and demonstrate the effectiveness of this model and its potential applicability to other attractions. These findings provide valuable insights for decision makers to improve services and to increase visitor engagement.

Keywords

• sentiment analysis
• NLP
• large language model (LLM)
• RoBERTa
• transfer learning
• tourism