Sentiment Analysis of Restaurant Reviews in Artvin Province by Rule-based Sentiment Analysis and Machine Learning

Abstract

The purpose of this study was to investigate customer sentiments of restaurants in Artvin province. It was determined that 73.9% of the reviews were positive, and 26.1% were negative. 7 topics including place, view, price, food, service, staff and taste were extracted from the reviews. While the most reviews were about the place with 33.89%, it was followed by view with 15%, and the fewest reviews were about taste with 5.83%. It was found that the view topic was the most liked among these topics. 23.53% of those who commented on the price stated that the prices were high, while the percentage of those who indicated that the service was slow was 21.98%. In general, it was noticed that the service, place, food, and view topics were closely related to each other, and a customer who likes one of them is likely to appreciate the others and vice versa. It can be concluded that the application of RBSA and ML methods together is appropriate in terms of enabling both grammar rules and artificial intelligence methods and obtaining satisfactory results.

Keywords

• Artvin Restaurant
• sentiment
• rule-based sentiment analysis
• machine learning
• Artvin

Sentiment Analysis of Restaurant Reviews in Artvin Province by Rule-based Sentiment Analysis and Machine Learning

Abstract

Bu çalışmanın amacı Artvin ilindeki restoranların müşteri duygularını araştırmaktır. Müşteri değerlendirmelerin %73.9'unun olumlu, %26.1'inin olumsuz olduğu belirlenmiştir. Yorumlardan; yer, manzara, fiyat, yemek, servis, personel ve lezzet olmak üzere 7 farklı başlık elde edilmiştir. En fazla yorum %33.89 ile yer hakkında yapılırken, bunu %15 ile manzara takip etmiş ve en az yorum ise %5.83 ile lezzet hakkında yapılmıştır. Bu başlıklar arasında en beğenilen başlığın manzara olduğu tespit edilmiştir. Fiyat hakkında değerlendirme yapan müşterilerin %23.53'ü fiyatların yüksek olduğunu belirtirken, servisin yavaş olduğunu belirtenlerin oranı ise %21.98 olmuştur. Genel olarak servis, yer, yemek ve manzara başlıklarının birbiriyle yakından ilişkili olduğu ve bunlardan birini beğenen ya da beğenmeyen müşterinin diğerlerini de beğenme/beğenmeme durumunun yüksek olduğu görülmüştür. Hem dil bilgisi kurallarının hem de yapay zeka yöntemlerinin kullanılması ve doğru sonuçların elde edilmesi açısından RBSA ve ML yöntemlerinin birlikte kullanılmasının uygun olduğu sonucuna varılabilir.

Keywords

• Artvin Restoran
• duygu
• kural tabanlı duygu analizi
• makine öğrenme

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