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In order to enhance the risk control efficiency of civil aviation flight safety in China and accurately identify the key risk factors that cause flight accidents, multi-source text mining of flight accident risks was conducted using Weibo information, news reports, and aviation accident investigation reports as samples. Flight accident risk factors were identified using the bidirectional encoder representations from transformers for topic modeling(BERTopic) . The semantic correlation of risk factors was analyzed using the Word2Vec model and complex network, from which the key risk factors were determined. The bidirectional encoder representations from transformers(BERT) was adopted to mine the personnel risk factors that trigger the most serious negative emotions among the public. The key personnel risk factors in low-altitude airspace were identified through word frequency statistics. The results indicate that personnel risk is the key risk factor leading to flight accidents. Among them, failure to strictly follow operating procedures, bird strikes, and sickness of flight crew are the key risk factors affecting flight safety. The non-strict implementation of operation procedures by flight crew not only arouses the most negative public emotions but also constitutes the key personnel risk factor leading to low-altitude airspace accidents.

, authors=Ze TIAN, Fan LUO, authorsList=Ze TIAN, Fan LUO, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1282030089529430824, articleId=1282030087495193380, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于多源文本挖掘的飞行事故关键风险识别, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为提升我国民用航空飞行安全风险管控效能，精准识别引发飞行事故的关键风险因素，以微博资讯、新闻报道、航空事故调查报告为样本，开展飞行事故风险多源文本挖掘，并借助基于双向编码器的主题模型（BERTopic）识别飞行事故风险因素；运用Word2Vec模型和复杂网络解析风险因素的语义关联，确定关键风险因素；采用双向编码器（BERT）挖掘出引发公众最严重负面情绪的人员风险因素，并结合词频统计方法辨识低空空域的关键人员风险因素。结果表明：人员风险是导致飞行事故的关键风险，其中未严格执行操作程序、鸟击和机组成员疾病是影响飞行安全的关键风险因素；飞行机组人员未严格执行操作程序引发的公众负面情绪最为强烈，也是低空空域事故的关键人员风险因素。

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田泽（1995—），男，湖南湘西人，博士研究生，主要研究方向为安全风险管理。E-mail:tianze2025@126.com。

"}, bioImg=null, bioContent=

田泽（1995—），男，湖南湘西人，博士研究生，主要研究方向为安全风险管理。E-mail:tianze2025@126.com。

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