Araştırma Makalesi

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

Cilt: 37 Sayı: 2 30 Eylül 2025
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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

Kaynakça

  1. Al-Otaibi S T, Rasheed A. Review and Comparative Analysis of Sentiment Analysis Techniques. Informatica. 2022; 46 (1): 33–44
  2. Hai Z, Kim K C J ve Yang C. Identifying features in opinion mining via intrinsic and extrinsic domain relevance. IEEE Trans Knowl Data Eng. 2014; 26 (3): 634.
  3. Cui J, Wang Z ve Cambria E. Survey on sentiment analysis: evolution of research methods and topics. Artificial Intelligence Review. 2023; (56): 8469–8510.
  4. Taherdoost E ve Madanchian M. Artificial Intelligence and Sentiment Analysis: A Review in Competitive Research. Computers, 2023; 12 (37).
  5. Khan M T, Durrani M ve Ali A. Sentiment analysis and the complex natural language. Complex Adapt Syst Model. 2016; 4 (2).
  6. Ramadhan F, Sitanggang A, Wibawa J ve Radliya N. Implementation of Digital Marketing Strategy with Chatbot Technology. Int. J. Artif. Intell. Res. 2023; 7 (2): 132.
  7. Wu S ve Gao Y. Machine Learning Approach to Analyze the Sentiment of Airline Passengers’ Tweets. Transp. Res. Rec. 2023; 2678 (1).
  8. Patel A, Oza P ve Agrawal S. Sentiment Analysis of Customer Feedback and Reviews for Airline Services using Language Representation Model. Procedia Comput. Sci. 2023; 218: 2459–2467.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Duygusal Bilgi İşleme, Makine Öğrenme (Diğer), Veri Madenciliği ve Bilgi Keşfi, Doğal Dil İşleme

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

30 Eylül 2025

Gönderilme Tarihi

29 Mayıs 2025

Kabul Tarihi

29 Eylül 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 37 Sayı: 2

Kaynak Göster

APA
Koçak, H. (2025). A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 37(2), 909-918. https://doi.org/10.35234/fumbd.1708787
AMA
1.Koçak H. A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2025;37(2):909-918. doi:10.35234/fumbd.1708787
Chicago
Koçak, Hakan. 2025. “A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 37 (2): 909-18. https://doi.org/10.35234/fumbd.1708787.
EndNote
Koçak H (01 Eylül 2025) A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 37 2 909–918.
IEEE
[1]H. Koçak, “A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most”, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, c. 37, sy 2, ss. 909–918, Eyl. 2025, doi: 10.35234/fumbd.1708787.
ISNAD
Koçak, Hakan. “A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 37/2 (01 Eylül 2025): 909-918. https://doi.org/10.35234/fumbd.1708787.
JAMA
1.Koçak H. A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2025;37:909–918.
MLA
Koçak, Hakan. “A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, c. 37, sy 2, Eylül 2025, ss. 909-18, doi:10.35234/fumbd.1708787.
Vancouver
1.Hakan Koçak. A Generative AI-Driven Analysis of Airline Passenger Feedback: Revealing What Matters Most. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 01 Eylül 2025;37(2):909-18. doi:10.35234/fumbd.1708787