重大突发公共卫生事件中的舆情特征及演化分析:以新冠肺炎疫情为例

Text mining of the media coverage of major public health emergencies: a case study of COVID-19

  • 摘要:
    目的本文利用文本挖掘前沿技术,基于新型冠状病毒肺炎(简称:新冠肺炎)疫情媒体新闻报道的文本分析,了解我国重大突发公共卫生事件发展趋势、以及政府和社会主体的应对机制。
    方法采用主题模型的方法,从新闻报道的数量分布、主题内容、发展趋势、情感倾向四个角度对新冠肺炎的媒体报道进行文本分析。
    结果新冠肺炎疫情媒体报道、新闻评论与疫情发展呈大体一致的走势。政府的应对措施是媒体报道的主体,社会力量、医学进展等类别新闻报道也受到一定的关注。不同主题的发展趋势因其属性不同,而呈现持续性或阶段性波动的特征。
    结论主题模型方法较为全面展示了新冠肺炎疫情网络舆情的发展和政府应对过程,基于主题模型的报道类别和构成特征,为完善国家公共应急管理体系提供了新的研究视角。

     

    Abstract:
    ObjectiveBased on the text analysis of COVID-19 media report, text mining was used to probe the trend of major public health emergencies and response of the government and social subjects in China.
    MethodsUsing the topic model method, we focused on the quantity of news report, topic content, development trend, and emotional tendency, to present the characteristics of media report on China's public health emergency, and the response mechanism of the Chinese government and the whole society.
    ResultsThe media report and news commentary of COVID-19 showed a consistent trend with the epidemic progress. The governmental response was the main target of media report, while social power, medical progress and other categories also attracted some attention. The development trend of different topics was characterized by continual or periodic variation due to their different attributes.
    ConclusionThe topic model method comprehensively demonstrates the development and response process of the COVID-19 epidemic. The model may provide a new perspective to improve the national public emergency management system.

     

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