Abstract

This preliminary study explores the use of Big Data analytics in the public administration of Türkiye’s tourism sector, focusing on the extraction and analysis of visitor reviews from the TripAdvisor platform. The primary objective is to compile a comprehensive database of records for 262 museums and archaeological sites, managed by the Turkish Ministry of Culture and Tourism, distributed across 64 provinces. Using web scraping techniques, over 72,500 reviews written in English were collected, representing approximately 49% of the total available reviews for these attractions. he methodology involves sentiment analysis to assess visitor perceptions, highlighting both positive and negative feedback. The analysis identifies common themes such as the admiration for historical and cultural significance, and criticisms regarding logistical issues like ticket

prices and crowd management. The study emphasizes the importance of such detailed feedback in informing public decision-making processes, aiming to enhance the quality and appeal of Türkiye’s diverse tourism offerings. Findings from this analysis reveal that reviews are heavily concentrated in major tourist hubs such as Istanbul, Antalya, and Izmir, with attractions like the Ayasofia Museum/Mosque and Topkapı Palace receiving the most feedback. This geographical and thematic concentration of reviews provides valuable insights into visitor preferences and areas requiring improvement. The study concludes that integrating Big Data analytics into public administration can significantly benefit the tourism sector, leading to better-informed policies and strategic enhancements that could boost tourism revenues and visitor.

Keywords: Big Data, Tourism, Web Scraping, Sentiment Analysis, Türkiye.

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