Koh Larn, a small island located approximately 7.5 kilometres off the coast of Pattaya City, Chon Buri Province, receives over three million visitors annually, one of Thailand’s highest-traffic island destinations. Its easy ferry access from Pattaya and proximity to Bangkok have fuelled sustained tourism growth, yet this popularity has brought mounting environmental pressures: coastal degradation, unmanaged solid waste, deteriorating water quality, and chronic overcrowding at beaches and piers. Conventional sustainability assessments, relying on periodic surveys or annual waste statistics, tend to identify problems only after damage has occurred, leaving managers without the real-time intelligence needed for timely intervention. This study addresses that gap by applying machine-learning sentiment analysis to 2,388 English-language TripAdvisor reviews (2015–2024), transforming unstructured tourist feedback into actionable sustainability diagnostics. Findings are situated within two complementary policy frameworks: the UN Sustainable Development Goals (SDGs) and the Blue Economy, which calls for sustainable use of marine resources while advancing social equity and economic resilience. Together, these frameworks reveal that Koh Larn’s tourism model remains trapped in a short-term, extractive paradigm, prioritising visitor volume over ecological health. This research offers a data-driven roadmap to shift the island toward regenerative, SDG-aligned stewardship of its marine and coastal assets.
This project aims to develop a data-driven approach for detecting sustainability gaps in island tourism and translating those findings into actionable SDG-aligned policy. The study pursues three core objectives:
1. To apply machine-learning sentiment analysis to international tourist reviews of Koh Larn, identifying recurring operational and environmental failures from the tourist perspective.
2. To map identified sustainability gaps onto specific SDG targets and Blue Economy pillars, clarifying which international sustainability commitments are being undermined by current tourism management.
3. To formulate a practical Blue Tourism Strategy for Koh Larn that guides local managers and policymakers toward regenerative, ecologically responsible destination management.
This study employed a mixed-methods design integrating machine learning, qualitative content analysis, and SDG–policy mapping. A corpus of 2,388 English-language tourist reviews of Koh Larn was collected from TripAdvisor (2015–2024) using automated web scraping, then preprocessed through tokenisation, stop-word removal, and lemmatisation. Five supervised machine-learning algorithms were trained and compared; the Support Vector Machine (SVM) achieved the highest performance (accuracy 87.29%, F1-score 75.38%) and was selected for full sentiment classification. The 90 negative reviews identified were then subjected to qualitative content analysis, coding each review into five problem categories: Scenery, Facility, Staff and Service, Safety, and Accessibility. Finally, each identified issue was mapped onto specific SDG targets and Blue Economy pillars to pinpoint which sustainability commitments were being undermined, and findings were translated into a structured policy framework — the Koh Larn Blue Tourism Strategy.
This study identified five critical sustainability failure domains in Koh Larn’s tourism: environmental degradation (Scenery, 37.44%), inadequate infrastructure (Facility, 29.05%), poor service quality (Staff and Service, 19.55%), safety risks (Safety, 10.61%), and access barriers (Accessibility, 3.35%). These failures were found to directly undermine four SDG targets, SDG 9, 11, 12, and 14, confirming that the island’s tourism model remains driven by short-term extraction rather than regenerative stewardship. Beyond diagnostics, the research produced three tangible impacts. Methodologically, it validated machine-learning sentiment analysis as a reliable, low-cost tool for real-time sustainability monitoring — applicable to other coastal destinations across Thailand and the region. Policy-wise, it delivered the Koh Larn Blue Tourism Strategy: a concrete action framework covering zero-plastic initiatives, eco-infrastructure upgrades, Eco-Service Certification, and a Marine Governance and Risk Committee. Academically, it advanced the integration of digital analytics with the SDGs–Blue Economy nexus, offering a transferable model for data-driven sustainable destination management globally.
Project Leader: Assoc. Prof. Dr. Narong Pleerux
