TY - JOUR T1 - “Recommend or not Recommend” Topic Modelling of User Reviews in Airline Market TT - “Önermek Ya Da Önermemek” Havayolu Pazarında Kullanıcı Yorumlarının Konu Modellemesi AU - Pınarbaşı, Fatih PY - 2025 DA - April Y2 - 2025 DO - 10.25287/ohuiibf.1556680 JF - Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi JO - ÖHÜİİBFD PB - Niğde Ömer Halisdemir Üniversitesi WT - DergiPark SN - 2564-6931 SP - 586 EP - 599 VL - 18 IS - 2 LA - en AB - Understanding customers and the market in the airline industry, which has unique characteristics such as a competitive environment, diverse consumer expectations, and different service levels, is critical for marketing decision-making. Digital platforms offer valuable information sources through online reviews to companies, and it is essential to evaluate the data to evaluate the customers. The study aims to discover the topics in airline user reviews from a duality perspective by recommending reviews and not-recommending reviews. Consistent with the study aim, topic modeling methodology through BERTopic transformers-model is employed to detect the topics included in Skytrax online reviews on Airlinequality.com. 33.810 user reviews from 25 airline companies are used as the study sample. Individual topics detected by topic modeling methodology are grouped into topic groups in the study. Five main topic groups (flight experience, customer service, travel class, airline mentions, and other) for recommending status user reviews, and nine main topics groups (flight experience, service experience, customer service/operations, baggage, customer expressions, region/country-based expressions, seats, transferring process and special cases) for not-recommending status user reviews are concluded in the study. KW - airline marketing KW - user recommendation KW - online reviews KW - word of mouth N2 - Rekabetçi bir ortam, farklı tüketici beklentileri ve farklı hizmet seviyeleri gibi kendine özgü özelliklere sahip havayolu endüstrisinde müşterileri ve pazarı anlamak, pazarlama karar alma süreçleri için kritik öneme sahiptir. Dijital platformlar, şirketlere çevrimiçi yorumlar aracılığıyla değerli bilgi kaynakları sunar ve müşterileri değerlendirmek için verileri değerlendirmek önem arz etmektedir. Çalışma, havayolu kullanıcı değerlendirmelerindeki konuları, öneren ve önermeyen değerlendirmeler üzerinden iki yönlü bir bakış açısından keşfetmeyi amaçlamaktadır. Çalışmanın amacına uygun olarak, Airlinequality.com'daki Skytrax çevrimiçi değerlendirmelerinde yer alan konuları tespit etmek için BERTopic dönüştürücü modeli aracılığıyla konu modelleme metodolojisi kullanılmıştır. Çalışmada örneklem olarak 25 havayolu şirketine dair 33.810 kullanıcı yorumu kullanılmıştır. 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