Sentiment of Chinese Tourists towards Malaysia Cultural Heritage Based on Online Travel Reviews

Abstract

Analyzing the perception differences and influencing factors of cross-cultural groups in heritage tourism can help heritage sites to formulate differentiated service and improve tourist satisfaction. This research adopted the BERT model to undertake sentiment analysis of 17,555 Chinese online reviews for nine scenic spots in Melaka. Using vocabulary filtering, co-occurrence analysis, and semantic clustering technology, the emotional characteristics of Chinese outbound tourists when they visited heritage sites in Melaka were analyzed, which revealed the factors influencing their positive and negative emotions. Results showed that: 1. The BERT-based deep learning approach can obtain improved sentiment predictive performance. 2. Chinese tourists’ general emotional perceptions of Melaka were positive and they were very interested in heritage sites. 3. The most important reason for the negative emotions of Chinese tourists was a lack of cultural experience in Melaka. This research expands the application of deep learning in the field of tourism, and it helps heritage tourism destinations to improve their marketing plans for Chinese tourists and achieve long-term sustainable development of the destination.