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

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Fırat Üniversitesi Mühendislik Bilimleri Dergisi
Cilt: 37 Sayı: 2
A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most

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

Pages : 909-918

View : 23 | Download : 29

Publication Date : 2025-09-30

Article Type : Research Paper

Abstract :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.
Keywords : Müşteri yorumları analizi, doğal dil işleme, büyük dil modelleri, üretken AI, google gemini

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