Abstract
The development of technology creates new phenomena that affect tourist behavior after visiting tourism destinations, one of the examples is exchange travel information and opinion of satisfaction or dissatisfaction with travel experiences through online review sites. The purpose of this research is to gain a deeper understanding of perceived destination-based tourism quality (TOURQUAL) using big data approach. This research applied selected text mining methods to investigates tourists’ perceptions of Borobudur. User-generated content collected from TripAdvisor between 2016 and 2019 were processed. Through sentiment analysis, Borobudur has a good service quality with 83.4% positive and 16.6% negative sentiments. Then, all reviews were grouped into six TOURQUAL attributes using multiclass classification. The top 3 positive attributes are access, experience, and technical quality. Through a text network analysis, we found the summary of tourists’ perceptions in the form of a network of the most frequent words used in social conversation. This research derives insights that useful to help businesses, especially the tourism industry to understand their visitors in a better way to improve their service quality performance.
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