Makine Öğrenmesi ile Çevrimiçi Otel Yorumlarının Değerlendirilmesi: Duygu Analizi ve Konu Modelleme ile Derinlemesine Bakış

Öz

Turizm sektörü içerisinde bulunan seyahat platformlarına yapılan çevrimiçi kullanıcı değerlendirmeleri, otel işletmelerinin hizmet kalitesini ve sahip olduğu tüketici memnuniyetinin belirlenmesinde önemli bir faktör haline gelmiştir. Bu kapsamda ilgili turizm platformlarındaki bilgi birikiminin artması, otel yönetimlerinin büyük veri kapsamında kullanılan yöntemler ile çevrimiçi kullanıcıların yaptığı değerlendirmelerin net bir şekilde anlamasını sağlamaktadır. Bu değerlendirmelerin yapısal ve anlamsal özelliklerinin analiz edilmesi, otellerin misafir memnuniyet düzeyini etkileyen unsurları bulmalarına yardım etmektedir. Bu gelişmeler kapsamında bu çalışmada Türkiye’nin önemli bir turizm destinasyonu olan Alanya şehrinde bulunan otellerin çevrimiçi yorumları, makine öğrenmesi tabanlı doğal dil işleme ve metin madenciliği teknikleri kullanılarak analiz edilmiştir. Yorumların müşteri memnuniyeti durumunun analizi için duygu analizi, içermiş olduğu konuların ortaya çıkarılması için ise konu modelleme yöntemleri veri setine uygulanmıştır. Ayrıca çalışmada ortaya konan duygu sınıfları için hangi konuların bu sınıflara en fazla etkiye sahip olduğunu anlamaya yönelik ise lojistik regresyon analizi ek olarak yapılmıştır. Araştırma sonucunda otelin sahip olduğu olanaklar, animasyon ve personel konuları, misafirlerin memnuniyetine en fazla olumlu yansıyan konular olurken, önbüro ve oda konularının ise daha çok olumsuz duygularla ifade edildiği ortaya çıkmıştır.

Anahtar Kelimeler

• Turizm İşletmeciliği
• Otel
• Makine Öğrenmesi
• Konu Modelleme
• Duygu Analizi
• Alanya

Evaluating Online Hotel Reviews with Machine Learning: Insights from Sentiment Analysis and Topic Modeling

Öz

User generated content platforms in tourism industry have become a significant factor according to determine customer satisfaction and service performance of hotel businesses. In this context, the increase in information on tourism platforms has enabled hotel managements to understand their shares more clearly by using several methods in the scope of big data management. Analyzing the structural and semantic features of online reviews helps hotel managements better find out the factors influencing guest satisfaction level. Taking into consideration of this fact, online reviews of hotels which located in Alanya, one of the Turkey's major tourism destinations, were analyzed using machine learning-based natural language and text mining techniques. Topic modeling and sentiment analysis were implemented into dataset to identify the most frequently mentioned topics and their impact on customer satisfaction level. Furthermore, logistic regression analysis was performed to achieve which topics have the most influence for the determined sentiment classes. The results show that amenities, animation and staff-related topics have the most positive influence on topics on satisfaction, whereas front desk and room-related topics are associated with negative sentiments.

Anahtar Kelimeler

• Tourism Management
• Otel
• Machine Learning
• Topic Modeling
• Sentiment Analysis
• Alanya

Kaynakça

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