Authors - Chirani Perera, Uvini Ranaweera, Indra Mahakalanda Abstract - This study investigates tourist perceptions of seven southern beaches in Sri Lanka using Google Reviews. With the increasing influence of online plat-forms in travel decision-making, analyzing review content provides valuable in-sights into tourist experiences and preferences. The research employs trans-former-based models from Hugging Face for sentiment analysis and topic modeling, offering a modern, data-driven approach to textual review interpretation. Word clouds and bigram visualizations are used to highlight common positive and negative expressions associated with each beach. The findings reveal themes such as cleanliness, natural beauty, surfing opportunities, crowd, and local ser-vice quality as key themes associated with the southern coastline of Sri Lanka. Sentiment patterns vary across beaches, with some consistently rated positively while others receive mixed feedback. This analysis offers practical insights for stakeholders in the field of tourism to improve destination management and marketing strategies. The study demonstrates the effectiveness of modern-day NLP techniques in understanding tourist experiences and provides a scalable frame-work for future such analysis that centres around the user responses.
