Data-Driven Decision-Making In Airlines: The Role of Sentiment Analysis and Emotion Detection

This paper uses the PRISMA methodology to explore the use of sentiment analysis (SA) and emotion detection (ED) within the airline industry. The re-search categorizes applications into four distinct areas: customer analysis (in which SA/ED techniques are used to process feedback from social media, re-view sites, and surveys, enhancing service quality and brand reputation); crisis management (focusing on the early detection of issues and timely responses during disruptions); business improvements (addressed through demand fore-casting, marketing optimization, and operational adjustments using SA/ED); and analytics techniques (which reveals a shift in SA/ED from traditional lexi-con-based methods to advanced machine learning, deep learning, and hybrid approaches). Overall, the findings highlight the potential of SA/ED for business strategies and data-informed decision-making within the aviation industry.