Türkiye’deki Otel Konuk Yorumları ve Puanlarının Metin Madenciliği ile Analizi

Konaklama tesislerindeki konuk yorumları ve verilen puanlar, günümüzde seyahat planlaması yapan misafirler için oldukça önemli bir faktör haline gelmiştir. İnternet üzerindeki seyahat acenteleri ve platformları, misafirlerin konaklama tercihlerini şekillendirmede kritik bir rol oynamaktadır. Bu platformlar, kullanıcıların gerçek deneyimlerini paylaşmasına ve diğer potansiyel misafirlere yol gösterici bilgiler sunmasına olanak sağlamaktadır. Seyahat acenteleri ve seyahat platformları, konaklama tesislerine ait kullanıcı yorumlarını ve verilen puanları genellikle detaylı bir şekilde sunmaktadır. Misafirler, otel veya diğer konaklama seçenekleri hakkında daha fazla bilgi edinmek, deneyimleri hakkında fikir sahibi olmak ve olumlu/negatif yönleri değerlendirmek için bu yorumlara güvenirler. Bu yorumlar, otelin temizlik düzeyi, hizmet kalitesi, personel yardımseverliği, konum avantajları, oda konforu, yiyecek ve içecek seçenekleri gibi birçok önemli unsuru içerebilir. Bu çalışma, Türkiye'deki konaklama tesisleri hakkında Türkçe olarak yapılan yorumları ve puanları metin madenciliği yöntemiyle analiz etmektedir. Bu amaçla, bir çevrimiçi seyahat acentesinden elde edilen Türkçe konaklama tesisleriyle ilgili yorumlar ve puanlar web madenciliği kullanılarak toplanmış ve ardından metin madenciliği işlemlerine tabi tutulmuştur. Çalışmada 60,252 Türkçe konuk yorumu ve puanı analiz edilmiştir. Türkiye'deki konaklama tesislerinin ortalama konuk puanı 3.93 olarak belirlenmiştir. Villa tipi tesisler en yüksek puanı almıştır (p=4.22; n=854). Coğrafi olarak, en yüksek puan İç Anadolu bölgesinde (p=4.07; n=5131), il olarak ise Nevşehir'de (p=4.53; n=2320) tespit edilmiştir. Metin madenciliği uygulaması sonucunda otel yorumlarında en sık tekrarlanan tekil kelimeler, puanlara göre gruplandırıldığında, misafirlerin 1 puan verdikleri tesisleri tavsiye etmedikleri, ancak 4 ve 5 puan verdikleri tesisleri tavsiye ettikleri ortaya çıkmıştır. Düşük puan verilen tesislerde, misafirlerin özellikle oda, kahvaltı, su ve temizlik konularında görüşlerini dile getirdikleri belirlenmiştir. Yüksek puan alan tesislerde ise misafirlerin otelin temiz olduğunu ve personelin misafirlerle ilgili olduğunu ifade eden kelimeler kullandıkları gözlemlenmiştir. Araştırma sonucunda, Türkiye'deki konaklama tesislerine yönelik Türkçe yorumlarda genel olarak, oda, kahvaltı, temizlik ve sıcak su sorunu gibi faktörlerin beğenilmeme ve dolayısıyla düşük puan verilmesine sebep olduğu tespit edilmiştir. Yüksek puan alımını etkileyen faktörlerin ise temizlik ve personelin ilgisiyle ilgili olduğu görülmektedir. Bu araştırmanın, sektör yöneticilerine, girişimcilere ve araştırmacılara, konuk memnuniyeti, konuk şikâyetleri ve memnuniyetle ilgili faktörlerin bilinmesi açısından katkı sağlayacağı düşünülmektedir. Türkiye'deki konaklama tesislerinin konuk yorumlarının metin madenciliği yöntemiyle analizini ele alan bu makaleden elde edilen sonuçlar, sektörün hizmet kalitesini ve konuk memnuniyetini artırmak için değerli bir rehber sağlamaktadır. Ayrıca, bu çalışma, gelecekteki araştırmalar için bir temel oluşturarak konaklama sektöründeki girişimciler ve akademisyenlere de yol gösterecektir.

Anahtar Kelimeler:

Metin Madenciliği, Otel Konuk Yorumları, Otel Konuk Puanları

Analysis of Hotel Guest Reviews and Ratings in Turkey with Text Mining

Guest reviews and ratings of accommodation facilities have become a very important factor for guests planning their trips today. Travel agencies and platforms on the Internet play a critical role in shaping guests' accommodation choices. These platforms allow users to share real-life experiences and provide guidance to other potential guests. Travel agencies and travel platforms often provide detailed user reviews and ratings of accommodation facilities. Guests rely on these reviews to learn more about their hotel or other accommodation options, gain insight into their experience, and rate the positives and negatives. These comments can include many important factors such as the hotel's cleanliness level, service quality, staff helpfulness, location advantages, room comfort, and food and beverage options. This study analyses the comments and scores in Turkish about accommodation facilities in Turkey by text mining. For this purpose, reviews and ratings of Turkish accommodation facilities obtained from an online travel agency were collected using web mining and then subjected to text mining processes. In the study, 60,252 Turkish guest comments and scores were analysed. The average guest rating of accommodation facilities in Turkey was determined to be 3.93. Villa-type facilities got the highest score (p = 4.22; n = 854). Geographically, the highest score was found in the Central Anatolia region (p = 4.07; n = 5131), and the province was Nevşehir (p = 4.53; n = 2320). As a result of the text mining application, when the most frequently repeated single words in hotel comments were grouped according to scores, it was revealed that guests did not recommend the facilities they gave 1 point for, but the facilities they gave 4 and 5 points for. It was determined that in the facilities with low scores, guests expressed their opinions, especially on the room, breakfast, water, and cleanliness. In facilities with high scores, it has been observed that the guests use words that express that the hotel is clean and that the staff is related to the guests. As a result of the research, it has been determined that factors such as room, breakfast, cleaning, and hot water problems in Turkish comments on accommodation facilities in Turkey cause dislike and therefore low scores. It is seen that the factors affecting the high score are related to cleanliness and the interest of the staff. It is thought that this research will contribute to sector managers, entrepreneurs, and researchers in terms of knowing guest satisfaction, guest complaints, and factors related to satisfaction. The results obtained from this article, which deals with the analysis of guest reviews of accommodation establishments in Turkey by text mining, provide a valuable guide for improving the service quality and guest satisfaction of the sector. In addition, this study will guide entrepreneurs and academics in the hospitality industry by providing a basis for future research.

Keywords:

Text Mining, Hotel Customer Reviews, Hotel Customer Rates,

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