Üretken Yapay Zekâ Destekli Bir Havayolu Yolcu Geri Bildirimi Analizi: En Önemli Olanı Ortaya Çıkarmak

Yıl 2025, Cilt: 37 Sayı: 2, 909 - 918, 30.09.2025

Hakan Koçak

https://doi.org/10.35234/fumbd.1708787

Öz

Yoğun rekabetin yaşandığı havayolu endüstrisi, müşteri memnuniyetine büyük ölçüde dayanarak güçlü ve zayıf yönlerini değerlendirir. Çevrimiçi yolcu yorumları, müşterilerin görüşlerini, beklentilerini ve duygularını yansıtan zengin bir veri kaynağı sunar. Bu geri bildirimlerin analizi, havayollarının geliştirilmesi gereken alanları belirlemesine ve yolcular için en önemli olanı anlamasına yardımcı olur. Bu çalışma, 2024 yılında Trip Advisor web sitesinden toplanan Türk Hava Yolları yorumlarını yorumlamak için Google Gemini’nin sıfırdan yönlendirme (zero-shot prompting) yaklaşımını kullanarak, alan spesifik ince ayara gerek kalmadan modelin etkinliğini göstermektedir. Bulgular, algılanan hizmet kalitesini, performansını ve değeri etkileyen faktörleri ortaya koymakta ve üretici yapay zekânın uzmanlaşmış müşteri duygu analizindeki potansiyelini ve havayolu endüstrisindeki uygulamalarını göstermektedir.

Anahtar Kelimeler

Müşteri yorumları analizi , doğal dil işleme , büyük dil modelleri , üretken AI , google gemini

A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most

Öz

The airline industry, characterized by intense competition, relies heavily on customer satisfaction to assess strengths and weaknesses. Online passenger reviews provide a rich source of data, capturing customers’ opinions, expectations, and emotions. Analyzing this feedback helps airlines identify areas for improvement and understand what matters most to passengers. This study employs a zero-shot prompting approach using Google Gemini to interpret Turkish Airlines reviews from Trip Advisor in 2024, demonstrating the model’s effectiveness without domain-specific fine-tuning. The findings highlight factors influencing perceived service quality, performance, and value, illustrating the potential of generative AI in specialized customer sentiment analysis and its practical applications in the airline industry.

Anahtar Kelimeler

Customer review analysis , natural language processing , large language models , generative AI , google gemini

Kaynakça

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