摘要
为展现国内外新冠病毒感染疫情期间对社交媒体上显露的社会情绪的研究,采用文献研究的方法,在IET Inspec系列数据库、中国知网期刊数据库中检索2020-2022年发表的相关论文并进行比较分析。分析结果显示,国内外研究均证实了突发公共卫生事件会引发更多的负面情绪并影响认知评估,且都采用文本内容分析和情绪分析方法。国外研究多以推特为研究文本,大量运用机器学习方法,将样本扩至上百万、上千万甚至亿级,注重不同人群、不同时空的差异化综合分析;国内研究多以微博为研究样本,较多运用情绪词典进行情绪分析,样本相对较小,倾向于不同时间段的差异化分析。
In order to show the domestic and international studies on social emotions of the COVID-19 pandemic revealed on social media,a literature research method was used to retrieve relevant papers published from 2020 to 2022 in the databases of IET Inspec and CNKI to conduct a comparative analysis.The results showed that both domestic and foreign studies confirmed that public health emergencies trigger more negative emotions and affect cognitive assessment,all using textual content analysis and emotion analysis.Most of the foreign studies took Twitter as the research text and used machine learning to expand the sample to millions,tens of millions or even billions,focusing on the differentiated comprehensive analysis of different groups of people and different time and space;most of domestic studies took Weibo as the research sample and used emotion lexicon more often for analysis,with relatively small samples and inclined to differentiated analysis of different time periods.
作者
周晖
ZHOU Hui(China Labour and Social Security News,Beijing 100013,China)
出处
《中华医学图书情报杂志》
CAS
2022年第12期65-69,共5页
Chinese Journal of Medical Library and Information Science
关键词
社会情绪
信息流行病
主题建模
情绪词典
Social emotion
Information epidemic
Topic modeling
Emotion lexicon
