Floating markets in South Kalimantan are culturally significant heritage destinations whose contemporary reputation is increasingly shaped by user-generated content on digital platforms. This study analyzes public perceptions of these markets by applying a lexicon-based sentiment analysis framework to 300 reviews collected from TripAdvisor and Google Maps between 2023 and 2024. The analytical workflow included text normalization, tokenization, stop-word removal, and stemming, with feature representation generated through term frequency–inverse document frequency (TF-IDF). Sentiment polarity was determined using bilingual lexicon-based scoring and categorized into positive, neutral, or negative sentiments. The results indicate that 45% of reviews expressed positive sentiment, highlighting cultural distinctiveness and riverfront experiences; 35% were neutral and provided descriptive logistical information; and 20% were negative, emphasizing waste issues, overcrowding, pricing inconsistencies, and perceived reductions in authenticity. TripAdvisor reviews exhibited greater emotional polarization than those on Google Maps. The findings demonstrate that lexicon-based sentiment analysis offers a transparent and effective approach for multilingual tourism contexts, providing insights into how digital narratives contribute to destination image formation. The study offers practical implications for improving environmental management, regulating visitor flows, and enhancing communication transparency within heritage tourism settings. It also contributes theoretically by underscoring the informational role of neutral reviews within electronic word-of-mouth dynamics. Future work may integrate machine learning-based sentiment classifiers or multimodal data to enhance analytical precision and extend the applicability of sentiment analysis in digital tourism research.
Pratiwi et al. (Wed,) studied this question.