Feng, Si-HaiXin, Yao-JiaoXiong, Sheng-HuaChen, Zhen-SongDeveci, MuhammetGarcia-Zamora, DiegoPedrycz, Witold2024-05-192024-05-1920231562-24792199-3211https://doi.org10.1007/s40815-023-01510-4https://hdl.handle.net/20.500.12713/4912The massive spread of COVID-19 and the crash of China Eastern Airlines MU5735 have negatively impacted the public's perception of civil aviation safety, which further affects the progress of the civil aviation industry and economic growth. The aim of research is to investigate the public's perception of China's civil aviation safety and give the authorities corresponding suggestions. First, we use online comment collection and sentiment analysis techniques to construct a novel evaluation index system reflecting the public's greatest concern for civil aviation safety. Then, we propose two novel large-scale group decision-making (LSGDM) models for aggregating evaluation: (1) K-means clustering with a novel distance measure for evaluators combined with unsupervised K-means clustering in two-stage, (2) unsupervised K-means clustering for evaluators combined with unsupervised K-means clustering for processing evaluation in two-stage. Finally, we compare the characteristics of different models and use the average of the two models as the final evaluation results.eninfo:eu-repo/semantics/openAccessCivil AviationSafety Perception EvaluationOnline Comments AnalysisThe Large-Scale Group Decision-Making ModelN2s-Kmc AlgorithmArticle25832333259WOS:0009745305000012-s2.0-85152932316N/A10.1007/s40815-023-01510-4Q2