Gastronomi turizmi açısından müşteri değerlendirmelerinin metin madenciliği ile analizi

Year 2021, , 1295 - 1312, 31.12.2021

Ahmet Büyükeke , Tufan Özsoy

https://doi.org/10.31795/baunsobed.1025204

Cited By: 1

Abstract

Geçmişte bölgesel çeşitlilikle sınırlı olan beslenme alternatifleri zaman içinde olağanüstü artış göstermiştir. Yaşamı sürdürmenin temel unsuru olmasının yanı sıra hedonik tüketim olarak da ön plana çıkmıştır. Turistler için yöresel mutfağı keşfetmenin ve yemek yeme zevkinin çok önemli olduğu zaten biliniyor. Sosyal medya platformları turistler için karar vermede en etkili araç haline geldi. Turistlerin nereye gidecekleri, nerede kalacakları, ne yiyip içecekleri konusundaki kararlarını önemli ölçüde etkilerler. Bu araştırmanın temel amacı, birbirinden farklı konaklama alternatiflerine sahip Kaş ve Belek'te hizmet veren restoranların TripAdvisor yorumlarını analiz etmek ve anlamlandırmaktır. Bu amaç doğrultusunda 147 işletmeden 10,829 müşteri yorumu ile konu modelleme analizi, duygu analizi ve isim-varlık tanıma analizi gerçekleştirilmiştir. Yorumlar, 3 farklı konu başlığı (Deneyim, Yemek ve Atmosfer) altında gruplandırılmıştır. Yorumlardaki memnuniyet oranı Kaş için %89,52, Belek için %95,64'tür. Kaş ve Belek yorumlarından sırasıyla 800 ve 445 farklı yemek ismi keşfedilmiştir. En beğenilen yemekler: biber, domates, sarımsak ve baharat gibi soslar ile sunulan biftek, hamburger ve straganof gibi et yemekleridir.

Keywords

Gastronomi, Yemek turizmi, Müşteri yorumları, Metin madenciliği

A text mining analysis of customer evaluations in terms of gastronomy tourism

Abstract

Nutritional alternatives, which were limited to regional diversity in the past, have increased extraordinarily over time. Besides being the basic element to sustain life, it has come to the fore as hedonic consumption. It is already known that discovering the local cuisine and the pleasure of eating are very important for tourists. Social media platforms have become the most effective tool for tourists in making decisions. They significantly influence the decisions of tourists on where to go, where to stay, what to eat and drink. The primary aim of this research is to analyze and make sense of TripAdvisor reviews of restaurants serving Kaş and Belek, which have different accommodation alternatives. For this purpose, topic modeling, sentiment, and name-entity recognition analyzes were carried out with 10,829 customer comments from 147 businesses. Reviews are clustered under the most appropriate 3 distinct subjects (Experience, Food, and Atmosphere). The satisfaction level in the comments is 89.52% for Kaş and 95.64% for Belek. In total, 800 and 445 different food names were discovered in Kaş and Belek reviews, respectively. Most liked foods: Meat dishes such as steak, burger, and stroganoff with cream, pepper, tomato, garlic, and spicy sauces.

Keywords

Gastronomy, Food tourism, Customer reviews, Text mining

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