Study on Aviation Safety Management Analysis and Improvement Strategies for Aviation Services using Text Mining

This study applies text mining techniques to analyze aviation safety management and propose improvement strategies for aviation services. A comprehensive dataset of 6,297 aviation-related documents, including accident reports, customer feedback, and social media posts, was collected and analyzed to extract significant keywords and patterns related to both safety and service quality. Key safety-related terms such as “weather,” “in-flight safety,” “crash,” and “maintenance” were identified, while service-related keywords included “customer service,” “reservation,” “on-time performance,” and “customer satisfaction.” Sentiment analysis was further applied to assess the emotional tone associated with these keywords, showing that safety-related terms often correlated with negative sentiments like “dangerous,” “anxious,” and “unsafe,” whereas service-related terms were generally linked to positive sentiments such as “satisfactory,” “reliable,” and “convenient.” The findings emphasize the importance of utilizing real-time customer feedback and safety reports to not only enhance service quality but also strengthen safety protocols. By integrating insights from both safety and service aspects, this research contributes to the development of proactive strategies that can lead to improved customer experience and enhanced aviation safety management. The study also provides a foundation for future research and policy-making within the aviation industry.