Artificial intelligence assisted insights into Bali’s destination image: sentiment and thematic analyses of TripAdvisor reviews

Abstrak

This study applies sentiment and thematic content analyses based on natural language processing (NLP) to gain valuable insights into the perceived image of Bali as a tourist destination. This study addresses the gap in how to realize the benefits of big data analytics in applied research, by using more approachable tools for researchers with limited programming skills and coding experience. A total of 6,800 TripAdvisor reviews of Bali’s top 12 tourist attractions between May 2019 and April 2023 were scrapped. The authors used Bardeen.ai for data mining and Atlas.ti for qualitative data analyses. Sentiment analysis revealed an overwhelmingly positive sentiment (70.4%) towards Bali’s tourist attractions, indicating a positive destination image. Post-pandemic tourists tend to express more positive sentiments in their reviews compared to pre-pandemic. Thematic content analysis indicated that positive sentiments are strongly related to satisfaction, positive experiences, enjoyment, and excitement, while environmental concerns and dissatisfaction are potentially harmful to Bali’s destination image. The study provides valuable insights into tourists’ emotional sentiments, perceptions, and thematic patterns of behavior, which can inform tourism marketers and destination strategists, and contribute to the larger discussion of utilizing big data analytics in tourism marketing research.