新冠肺炎新闻选题回顾:以CNN和《中国日报》为例

Yue Yuan, Kan Liu, Yanli Wang
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引用次数: 1

摘要

目的本研究的目的是对COVID-19新闻文章的主题进行分析,以便更好地了解新闻主题之间的关系和演变,有助于从量化的角度管理信息。设计/方法/方法为了明确分析COVID-19新闻文章,本文提出了棱镜架构。本文以《中国日报》和CNN的疫情相关新闻为基础,对两家新闻机构的主题进行识别,阐明主题之间的关系,跟踪疫情发展过程中主题的变化,并将结果以直观、有说服力的方式呈现出来。分析结果显示,CNN的话题分布比《中国日报》更集中,前者侧重于政府相关信息,后者侧重于医疗。此外,疫情对CNN和《中国日报》的报道偏好也产生了很大影响。新闻话题的演变分析表明,新闻话题的动态变化与疫情进程密切相关。原创性/价值本文以新颖的视角审视COVID-19新闻报道的主题,为疫情初期的新闻报道提供新的理解。分析结果拓展了信息学相关研究的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reviewing topics of COVID-19 news articles: case study of CNN and China daily
PurposeThe purpose of this study is to analyze the topics of COVID-19 news articles for better obtaining the relationship among and the evolution of news topics, helping to manage the infodemic from a quantified perspective.Design/methodology/approachTo analyze COVID-19 news articles explicitly, this paper proposes a prism architecture. Based on epidemic-related news on China Daily and CNN, this paper identifies the topics of the two news agencies, elucidates the relationship between and amongst these topics, tracks topic changes as the epidemic progresses and presents the results visually and compellingly.FindingsThe analysis results show that CNN has a more concentrated distribution of topics than China Daily, with the former focusing on government-related information, and the latter on medical. Besides, the pandemic has had a big impact on CNN and China Daily's reporting preference. The evolution analysis of news topics indicates that the dynamic changes of topics have a strong relationship with the pandemic process.Originality/valueThis paper offers novel perspectives to review the topics of COVID-19 news articles and provide new understandings of news articles during the initial outbreak. The analysis results expand the scope of infodemic-related studies.
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