Characterizing News Report of the Substandard Vaccine Case of Changchun Changsheng in China: A Text Mining Approach.
Characterizing News Report of the Substandard Vaccine Case of Changchun Changsheng in China: A Text Mining Approach.
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基于文本挖掘的长春长生疫苗事件新闻报道特征化研究。
DOI：
10.3390/vaccines8040691
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发表时间：
2020-11-17
期刊：
影响因子：
7.8
通讯作者：
Yang X
中科院分区：
文献类型：
--
作者：
Zhou P;He Y;Lyu C;Yang X
背景：2018年7月，中国爆发了不合格疫苗事件，引发了国内外媒体的广泛报道。对丰富的文本信息进行提炼，有助于更好地理解这一公共事件中的人物。方法：我们收集了2018年7月15日至8月25日期间来自中国83家主流媒体的2211篇新闻报道文本，并使用结构话题模型（STM）来识别出现的主要话题和特征。我们还使用基于词典的情绪分析来揭示主题所表达的情绪以及它们的时间变化。结果：新闻报道的主题可分为六大类，包括：(1)媒体调查，(2)高层回应，(3)政府行为，(4)知识传播，(5)财经相关，(6)评论。话题的流行度在事件的不同阶段发生了变化，说明了政府的行动。人们的情绪通常从消极到积极，但根据不同的话题而有所不同。结论：疫苗新闻报道的特点在不同阶段受到不同主题的影响。社会情感和政府干预的相互作用驱动着话题的内在动力及其变化。
Background: The substandard vaccine case of that broke out in July 2018 in China triggered an outburst of news reports both domestically and aboard. Distilling the abundant textual information is helpful for a better understanding of the character during this public event. Methods: We collected the texts of 2211 news reports from 83 mainstream media outlets in China between 15 July and 25 August 2018, and used a structural topic model (STM) to identify the major topics and features that emerged. We also used dictionary-based sentiment analysis to uncover the sentiments expressed by the topics as well as their temporal variations. Results: The main topics of the news report fell into six major categories, including: (1) Media Investigation, (2) Response from the Top Authority, (3) Government Action, (4) Knowledge Dissemination, (5) Finance Related and (6) Commentary. The topic prevalence shifted during different stages of the events, illustrating the actions by the government. Sentiments generally spanned from negative to positive, but varied according to different topics. Conclusion: The characteristics of news reports on vaccines are shaped by various topics at different stages. The inner dynamics of the topic and its alterations are driven by the interaction between social sentiment and governmental intervention.
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5.9
作者：
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通讯作者：
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