Decoding Customer Sentiments in Turkish Airlines Mobile Apps: A Comprehensive Text Mining Approach

Abstract

This study investigates user feedback on mobile applications of Turkish airlines, focusing on the key factors contributing to user satisfaction and dissatisfaction. By utilizing advanced text classification techniques such as sentiment analysis and Latent Dirichlet Allocation (LDA), the research decodes customer reviews from the Google Play Store and Apple App Store. The analysis identifies prevalent themes in user feedback, including issues related to usability, app performance, and customer service responsiveness. The results reveal that app updates, functionality issues, and customer support are critical areas where airlines need improvement. This study provides actionable insights for Turkish airlines to optimize their mobile applications, ultimately enhancing customer satisfaction and loyalty.

Keywords

• Turkish airlines
• Mobile applications
• Sentiment analysis
• Customer satisfaction
• Text mining

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