Çevrim İçi Ziyaretçi Yorumlarının Derin Öğrenme Tabanlı Yöntem ile Analizi: Divriği Ulu Camii ve Darüşşifası Örneği

Abstract

Bu çalışma, Divriği Ulu Camii ve Darüşşifası’na yönelik çevrim içi ziyaretçi yorumlarını derin öğrenme tabanlı metin analizi yöntemleriyle inceleyerek, ziyaretçi deneyimlerini ortaya koymayı amaçlamaktadır. Bu kapsamda Google Haritalar platformundan elde edilen kullanıcı yorumlarından yararlanılmıştır. Çalışmada, kullanıcı tarafından oluşturulan içerikler, metin madenciliği, varlık temelli analizler, varlık eş-görülme ağları ve derin öğrenme tabanlı duygu analizi teknikleri kullanılarak çok boyutlu biçimde analiz edilmiştir. Bulgular incelendiğinde çevrim içi ziyaretçi yorumlarının büyük ölçüde mimari unsurlar etrafında şekillendiğini görülmektedir. Özellikle kapı, taş ve motif gibi yapısal öğeler, ziyaretçi yorumlarında öne çıkan temel unsurlar olarak belirlenmiştir. Bununla birlikte, ışık, gölge ve manevi atmosferi çağrıştıran ifadelerin mimari unsurlarla birlikte kullanılması, Divriği Ulu Camii ve Darüşşifası’nın yalnızca fiziksel bir yapı olarak değil, aynı zamanda deneyimsel ve duygusal bir mekân olarak algılandığını ortaya koymaktadır. Baskın olmasa da ulaşım ve altyapı gibi itici faktörler de ortaya çıkmasına rağmen genel duygu durumunun pozitif olduğu ve özellikle şaşkınlık ile sevgi duygularının ön plana çıktığı görülmektedir. Elde edilen bulgular, çevrim içi ziyaretçi yorumlarının kültürel miras alanlarının algılanan değeri, ziyaretçi deneyimi ve duygusal etkilerini anlamada güçlü bir veri kaynağı sunduğunu göstermekte olup, kültürel miras yönetimi ve dijital tanıtım stratejileri açısından önemli çıkarımlar sunmaktadır.

Keywords

• Kültürel Miras Turizmi
• Divriği Ulu Camii ve Darüşşifası
• Çevrim İçi Yorum
• Derin Öğrenme
• Duygu Analizi

Analysis of Online Visitor Reviews Using a Deep Learning-Based Method: The Case of Divriği Great Mosque and Hospital

Abstract

This study aims to explore visitor experiences by analyzing online visitor reviews related to the Divriği Great Mosque and Hospital using deep learning based text analysis methods. In this context, user-generated reviews obtained from the Google Maps platform were utilized as the data source. The study employs a multidimensional analytical framework that includes text mining techniques, entity-based analyses, entity co-occurrence networks, and deep learning based sentiment analysis. The findings indicate that online visitor narratives are largely shaped around architectural elements. In particular, structural components such as doors, stonework, and motifs emerge as the most prominent features in visitor reviews. Moreover, the frequent co-occurrence of architectural elements with expressions referring to light, shadow, and spiritual atmosphere suggests that the Divriği Great Mosque and Hospital is perceived not only as a physical structure but also as an experiential and emotionally engaging space. Although push factors such as transportation and infrastructure issues are occasionally mentioned, they are not dominant in the overall discourse. Sentiment analysis results reveal that the general emotional tone of the online reviews is predominantly positive, with emotions of surprise and love standing out most prominently. Overall, the findings demonstrate that online visitor reviews constitute a valuable data source for understanding the perceived value, experiential dimensions, and emotional impacts of cultural heritage sites. The study further offers important implications for cultural heritage management and digital promotion strategies.

Keywords

• Cultural Heritage Tourism
• Great Mosque and Hospital of Divriği
• Online Reviews
• Deep Learning
• Sentiment Analysis

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