Visitor perceptions of over tourism: Text-mining insights from Seoul and Bali

<p class="MsoNormal" style="text-align: justify; text-justify: inter-ideograph; line-height: 120%; layout-grid-mode: char; mso-layout-grid-align: none; punctuation-wrap: simple; margin: 12.0pt 0cm 6.0pt 0cm;"><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 120%; font-family: 'Times New Roman',serif; mso-ansi-language: EN-US;">This study examines the impact of overtourism on visitor experiences in Bali, Indonesia, and Seoul, South Korea, by analyzing online user-generated reviews from popular tourist locations. The selected sites in Seoul include Myeongdong Shopping Street, Bukchon Hanok Village, and Hongdae Street, while Bali’s sites comprise Penglipuran Village, Kuta Beach, and Seminyak. A total of 1080 reviews per city (360 per location) were collected to ensure a robust and balanced dataset for comparative analysis. To extract visitor perceptions related to congestion, crowding, and other overtourism indicators, reviews were sourced using Outscraper.com, a web-based data extraction tool. A keyword-based filtering approach was applied, focusing on terms such as “noisy,” “traffic,” and “tourist” to identify relevant reviews that reflect visitor concerns about overcrowding and its associated effects. To maintain objectivity and representativeness, 360 reviews per location were randomly selected from the filtered dataset, ensuring a balanced sample of visitor opinions across both urban and island-based tourism destinations. By applying text-mining techniques, this study uncovers key themes and sentiment patterns that define visitor experiences in over-touristed areas. The findings offer valuable insights for tourism stakeholders seeking to mitigate the negative effects of overtourism while improving destination sustainability and visitor satisfaction.</span></p>