Mapping Tourist Sentiments Through Lexicon-Based Analysis of Social Media Reviews: The Case of Salak Sibetan Agritourism

Salak Sibetan, Bali's emblematic snake fruit cultivated in Sibetan Village, Karangasem, has gained increasing digital visibility through user-generated content across social media platforms. This study applies a bilingual lexicon‑based sentiment analysis framework integrating Indonesian and English sentiment lexicons, explicit negation handling, domain‑specific agritourism vocabulary, and a mean‑based sentiment scoring function to classify 500 online reviews collected from Facebook, Instagram, Shopee, TikTok, and Twitter/X. The methodology adapts Indonesian and English lexicons with negation handling, domain-specific refinement for agritourism terminology, and mean-based scoring to improve neutrality discrimination. Results indicate an overall sentiment distribution of 40% positive, 40% neutral, and 20% negative. Positive reviews emphasize taste quality (manis legit, renyah, fresh) and cultural authenticity, while negative feedback highlights packaging issues, inconsistent quality, and pricing concerns. Image‑centric platforms (Instagram and TikTok) exhibit higher proportions of positive sentiment emphasizing taste quality and authenticity, whereas transaction‑oriented platforms (Shopee and Twitter/X) show more neutral and negative expressions related to logistics, packaging, and pricing. Beyond sentiment measurement, the study demonstrates how lexicon‑based methods can capture platform‑specific evaluative behavior within heritage agritourism contexts, offering methodological insights for multilingual sentiment analysis in low‑resource domains and strategic implications for sustainable destination communication aligned with Sibetan’s FAO GIAHS recognition.