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Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach

机译:通过新闻媒体在中国Covid-19疫情的早期阶段通过新闻媒体进行健康沟通:数字主题建模方法

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Background In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. Objective The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. Methods We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. Results After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics’ themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. Conclusions Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media’s actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.
机译:背景技术2019年12月,少数冠心病病(Covid-19)案件在湖北武汉报道。不久之后,在中国其他地区检测到越来越多的病例,最终导致中国疾病爆发。随着这种可怕的疾病迅速传播,大众媒体通过提供有关该新型冠状病毒的健康信息,群体对Covid-19的社区教育处于积极的社区教育中,例如其发病机制,传播,预防和遏制。目的是本研究的目的是收集关于Covid-19的媒体报告,并调查媒体导向的健康通信模式以及媒体在中国在中国持续的Covid-19危机中的作用。方法采用WiseSearch数据库提取有关来自2020年1月1日至2020年2月20日之间的主要新闻媒体的相关新闻文章。然后,我们使用Python软件和Python Package Jieba进行排序和分析数据。我们寻求一个合适的主题编号,证明了一致性号码。我们使用合适的主题号和生成相应的关键字和主题名称进行潜在的Dirichlet分配主题。然后,我们通过通过多维缩放将它们绘制到2D平面中来将这些主题分成不同的主题。结果删除重复和无关报告后,我们的搜索确定了7791个相关新闻报道。我们列出了每天发布的文章数量。根据一致性值,我们选择了20个作为主题的数量并生成了主题的主题和关键字。基于主题可视化图,这些主题分为九个主要主题。最受欢迎的主要主题是预防和控制程序,医疗和研究,以及全球或地方社会和经济影响,占32.57%(n = 2538),16.08%(n = 1258)和11.79%(n = 919)分别收集的报告。结论新闻文章的主题建模可以生产关于质量媒体对早期健康沟通的重要性的有用信息。比较每天的文章数量和爆发发展,我们指出,中国的大众媒体新闻报道落后于Covid-19的发展。主要主题占了大约一半的内容,倾向于关注更大的社会而不是个人。 Covid-19危机已成为一个全球问题,社会担心捐赠和支持以及其他人之间的心理健康。我们建议未来的工作通过新闻数据的情感分析,在Covid-19危机期间解决了大众媒体对读者的实际影响。

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