Anıtkabir Yabancı Ziyaretçilerine Yönelik Makine Öğrenmesi Tabanlı Duygu Analizi

Öz

Duygu analizi, kullanıcı deneyimlerini anlamak, mekânsal algıyı değerlendirmek ve tasarım süreçlerini kullanıcı odaklı hale getirmek için kullanılan bir yöntemdir. Türk kültürünü ulusal kimlikle bütünleştiren anıtsal bir kompleks olan Anıtkabir, yerli ziyaretçilerde ulusal ve kültürel duygular uyandırırken, yabancı ziyaretçilerin zihninde farklı anlamlar ortaya çıkarmaktadır. Bu çalışma, 2021-2025 yılları arasında Anıtkabir’i ziyaret eden yabancı ziyaretçilerde mekânın peyzaj ve mimari özelliklerinin uyandırdığı duyguları makine öğrenmesi teknikleriyle ortaya koymayı amaçlamaktadır. Ziyaretçilerin algı ve değerlendirmelerini yansıtan Google Haritalar yorumları derlenerek anlamlı veriler elde edilmiştir. Veri seti, Parrott’un duygu sınıflandırma çerçevesine göre analiz edilmiş ve Lojistik Regresyon, Naive Bayes, Random Forest ve Destek Vektör Makineleri algoritmaları kullanılarak eğitilmiştir. Her bir modelin performans metrikleri ve tahmin doğruluğu ayrı ayrı ve karşılaştırmalı olarak değerlendirilmiştir. Sonuçlar, Lojistik Regresyon modelinin 0.78 F1-score değeriyle en yüksek performansı gösterdiğini ortaya koymuştur. Bulgular, Anıtkabir’in yabancı ziyaretçiler tarafından da tıpkı yerli ziyaretçiler gibi olumlu algılandığını ve kültürel miras alanlarının kültürler arası anlamlı duygusal deneyimler sunabildiğini göstermektedir. Genel olarak çalışma, Türkiye’nin en önemli kültürel ve ulusal simge mekânlarından biri olan Anıtkabir’in uluslararası ziyaretçiler tarafından nasıl algılandığını inceleyerek, kültürler arası mekân algısının duygusal boyutlarına ilişkin önemli çıkarımlar sunmaktadır. Ayrıca çalışma, kültürel miras alanlarında peyzaj ve mekânsal tasarım bileşenlerinin ziyaretçilerin duygusal deneyimleri üzerindeki etkisini ortaya koyarak, kullanıcı odaklı peyzaj planlama ve tasarım süreçlerine katkı sağlamaktadır.

Anahtar Kelimeler

• Anıtkabir
• Duygu Analizi
• Makine Öğrenmesi
• Yabancı Ziyaretçiler
• Parrott

Machine Learning-Based Sentiment Analysis for Foreign Visitors of Anıtkabir

Öz

Sentiment analysis is a method used to understand user experiences, evaluate spatial perception, and make design processes more user oriented. Anıtkabir, a monumental complex integrating Turkish culture with national identity, evokes national and cultural emotions among domestic visitors while generating different meanings for foreign visitors. This study aims to reveal the emotions evoked by Anıtkabir’s landscape and architectural features among foreign visitors between 2021 and 2025, using machine learning techniques. User comments shared on Google Maps were compiled to obtain meaningful data reflecting visitors’ perceptions and evaluations. The dataset was analyzed according to Parrott’s emotion classification framework and trained using Logistic Regression, Naive Bayes, Random Forest, and Support Vector Machine algorithms. Each model’s performance metrics and predictive accuracy were assessed individually and comparatively. The results showed that the Logistic Regression model achieved the highest performance with an F1-score of 0.78. Findings indicate that Anıtkabir is positively perceived by foreign visitors, similarly to domestic visitors, highlighting that cultural heritage sites can generate meaningful emotional experiences across cultures. Overall, this study contributes to understanding how one of Türkiye’s most significant cultural and national landmarks is experienced by international visitors, offering insights into the emotional dimensions of cross-cultural perception of heritage spaces. Furthermore, the study reveals the influence of landscape and spatial design components on visitors’ emotional experiences in cultural heritage sites, thereby contributing to user-oriented landscape planning and design processes.

Anahtar Kelimeler

• Anıtkabir
• Sentiment Analysis
• Machine Learning
• Foreign Visitors
• Parrott

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