Müşteri yorumlarının duygu analizi: konaklama işletmeleri
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Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
T.C. Maltepe Üniversitesi, Lisansüstü Eğitim Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Birbirine sıkı rakip olan Kemer ve Hanya bölgesindeki konaklama işletmeleri, sunmuş oldukları mal ve hizmetlerle müşterilerini memnun ederek pazarda daha büyük pay alma gayretindedirler. Konaklama işletmeleri bu amaçla rakip analizleri yaparak stratejik planlar hazırlamaktadır. Sunulan mal ve hizmetlerin müşteri tarafından nasıl algılandığı ve onlarda oluşan duygu durumu, hedeflerin ne kadar gerçekleştirildiğini gösterir. TripAdvisor web sitesindeki müşteri yorumlarının konaklama işletmelerinin değerlendirilmesi bakımından önemli bir veri kaynağı olduğu düşünülmektedir. Bu düşünceden hareketle, iki bölgedeki konaklama işletmelerinin 2015-2022 yılları arasındaki müşteri yorumları kazılmış, toplamda 197 binin üzerinde müşteri yorumu elde edilmiştir. Çeşitli normalizasyon işlemleri ve elemeler sonucunda 173 binden fazla yorum, 7 kategori (personel, oda konforu, ücretler, temizlik, rekreasyon, yiyecek içecek, otel genel) ve 26 alt boyutta parçalara ayrılmıştır. Veriler, makine öğrenmesi, nicel ve nitel veri analiz teknikleri kullanılarak analiz edilmiştir. Makine öğrenmesinde birçok metot denenmiş ve en yüksek başarıyı KNN metodu (%75) sağlamıştır. Yapılan çoklu doğrusal regresyon analizlerinde kategori ve boyutlardan elde edilen duygu puanlarının, müşterinin vermiş olduğu puanı açıklama oranı, kategori bazında %37,6, boyut bazında %37,9 olarak bulunmuştur. Veriler ayrıca bölge, sezon ve yıl değişkenlerine göre karşılaştırılmıştır. Rekreasyon kategorisi ve tüm alt boyutlarında ayrıca yiyecek içecek kategorisinin sadece tatlı, meyve ve snack büfe alt boyutlarında Kemer bölgesindeki konaklayan müşterilerin duygu puanının yüksek olduğu tespit edilmiştir. Diğer tüm kategori ve alt boyutlarda Hanya bölgesindeki konaklayan müşterilerin duygu puanlarının yüksek olduğu tespit edilmiştir. Sezon değişkenine göre yapılan analizlerde genel olarak düşük sezonda müşterilerin duygu puanlarının anlamlı derecede daha yüksek çıktığı tespit edilmiştir. Yıl değişkenine göre yapılan analizlerde, çoğu kategori ve alt boyutta geçmişten günümüze müşteri duygu puan ortalamalarının arttığı tespit edilmiştir. Ancak yiyecek içecek, personel, oda konforu kategori ve alt boyutlarında pandemi döneminde duygu puan ortalamalarının düştüğü, 2022 yılında yükselerek 2019 yılı seviyelerine çıktığı tespit edilmiştir. Tüm alt boyutlarda değişkenlere göre müşterilerin dilsel ifadeleri NVivo ve MAXQDA programları ile derinlemesine analiz ederek, sonuçlar olgusal olarak ortaya konulmuştur.
Accommodation businesses in Kemer and Chania, which are close competitors to each other, endeavour to get a bigger share in the market by satisfying their customers with the goods and services they offer. For this purpose, accommodation businesses prepare strategic plans by making competitor analyses. How the goods and services offered are perceived by the customer and their emotional state shows how much the objectives are realised. Customer comments on TripAdvisor website are considered to be an important data source for the evaluation of accommodation businesses. Based on this idea, customer reviews of accommodation establishments in two regions between 2015 and 2022 were excavated, and a total of over 197 thousand data were obtained. As a result of various normalisation processes and screening, more than 173 thousand comments were divided into 7 categories (staff, room comfort, fees, cleaning, recreation, food and beverage, hotel general) and 26 sub-dimensions. The data were analysed using machine learning, quantitative and qualitative data analysis techniques. Many methods were tried in machine learning and the KNN method (75%) provided the highest success. In the multiple linear regression analyses, the ratio of the emotion scores obtained from the categories and sub-dimensions to explain the score given by the customer was found to be 37.6% on category basis and 37.9% on sub-dimension basis in average. The data were also compared according to destination, season and year variables. In the recreation category and all sub-dimensions and only in the dessert, fruit and snack buffet sub-dimensions of the food and beverage category, it was found that the emotion scores of the customers staying in Kemer region were higher. In all other categories and sub-dimensions, it was determined that the emotion scores of the customers staying in Chania region were high. In the analyses made according to the season variable, it was determined that the emotion scores of the customers in the low season were significantly higher in general. In the analyses made according to the year variable, it was determined that the average customer emotion scores have increased in most categories and sub-dimensions from past to present. However, it was determined that in the categories and sub-dimensions of food and beverage, personnel, room comfort, the average emotion score decreased during the pandemic period, increased in 2022 and reached 2019 levels. The linguistic expressions of customers according to the variables in all sub-dimensions were analysed in depth with NVivo and MAXQDA programs and the results were presented factually.
Accommodation businesses in Kemer and Chania, which are close competitors to each other, endeavour to get a bigger share in the market by satisfying their customers with the goods and services they offer. For this purpose, accommodation businesses prepare strategic plans by making competitor analyses. How the goods and services offered are perceived by the customer and their emotional state shows how much the objectives are realised. Customer comments on TripAdvisor website are considered to be an important data source for the evaluation of accommodation businesses. Based on this idea, customer reviews of accommodation establishments in two regions between 2015 and 2022 were excavated, and a total of over 197 thousand data were obtained. As a result of various normalisation processes and screening, more than 173 thousand comments were divided into 7 categories (staff, room comfort, fees, cleaning, recreation, food and beverage, hotel general) and 26 sub-dimensions. The data were analysed using machine learning, quantitative and qualitative data analysis techniques. Many methods were tried in machine learning and the KNN method (75%) provided the highest success. In the multiple linear regression analyses, the ratio of the emotion scores obtained from the categories and sub-dimensions to explain the score given by the customer was found to be 37.6% on category basis and 37.9% on sub-dimension basis in average. The data were also compared according to destination, season and year variables. In the recreation category and all sub-dimensions and only in the dessert, fruit and snack buffet sub-dimensions of the food and beverage category, it was found that the emotion scores of the customers staying in Kemer region were higher. In all other categories and sub-dimensions, it was determined that the emotion scores of the customers staying in Chania region were high. In the analyses made according to the season variable, it was determined that the emotion scores of the customers in the low season were significantly higher in general. In the analyses made according to the year variable, it was determined that the average customer emotion scores have increased in most categories and sub-dimensions from past to present. However, it was determined that in the categories and sub-dimensions of food and beverage, personnel, room comfort, the average emotion score decreased during the pandemic period, increased in 2022 and reached 2019 levels. The linguistic expressions of customers according to the variables in all sub-dimensions were analysed in depth with NVivo and MAXQDA programs and the results were presented factually.
Açıklama
Anahtar Kelimeler
Turizm, Büyük veri, Makine öğrenmesi, Duygu analizi, Kategorizasyon, Regresyon, SWOT, Tourism, Big Data, Machine learning, Sentiment analysis, Categorisation, Regression, SWOT
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Aktaş, T. (2023). Müşteri yorumlarının duygu analizi: konaklama işletmeleri / Sentiment analysis of customer reviews: accommodation establishments. (Yayımlanmamış Doktora Tezi). Maltepe Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.
