摘要
目的探讨重庆市报告2022年内地首例输入性猴痘病例后新浪微博用户的情绪特点,为做好正确情绪引导和疾病防控宣传提供科学依据。方法利用微博平台下的微热点情绪分析模块,于2022年9月21日对以“重庆+猴痘”为关键词的微博数据源进行挖掘和情绪判别,排除已删除微博,并开展该关键词的各类情绪声量对比及其在不同属性(性别、认证类型)微博用户中所占比例的分析。结果共获取相关微博数194974条,其中中性情绪和愤怒情绪所占比例较高,分别为80088条(占41.08%)和41385条(占21.23%)。女性微博用户的情绪更为敏感,其中愤怒和悲伤情绪分别为32760条(占23.12%)和16113条(占11.37%)。敏感情绪所占比例较低的用户类型为拥有2000个以上粉丝的微博用户。情绪判别中出现较多的正面高频词为“健康”“坚持”和“容易”,负面高频词为“疫情”“病毒”和“吓人”。结论基于微博数据的情绪分析展示了微博用户参与猴痘话题讨论的情绪特点。女性在猴痘病例讨论中的情绪表现更为敏感,粉丝较多的微博用户的情绪表现更为谨慎,应注重对这两类人群的情绪正向引导。
Objectives To analyze the sentimental responses of Sina Weibo users to the first imported monkey⁃pox case report in the mainland of China in 2022,and to provide scientific evidence for guiding public emotions and publicizing disease prevention and control.Methods The micro-hotspots sentiment analysis module in Weibo platform was used to collect and classified the sentimental responses of Sina Weibo users based on the keywords of“Chongqing”and“Monkeypox”on September 21,2022.After excluding those deleted tweets,dif⁃ferent sentimental responses to the keywords were analyzed and compared.Results A total of 194974 related tweets were obtained,and most of them were neutral moods(80088,41.08%)and angry responses(41385,21.23%).Female users were more sensitive,with 23.12%(32760)of anger and 11.37%(16113)of sadness.Weibo users who had over 2000 followers were less sensitive.The most common positive words were“health”,“persistence”and“easy”,while the most common negative words were“epidemic”,“virus”and“scaring”.Conclusion The sentiment analysis based on Weibo data reveals different emotions of public participants on the topic of monkeypox.Women are more sensitive,and Weibo users with more followers are more cautious to pub⁃licly express their emotions.
作者
李怡
赵怡楠
熊鹰
姚宁
周爽
张春华
周春碚
LI Yi;ZHAO Yi-nan;XIONG Ying;YAO Ning;ZHOU Shuang;ZHANG Chun-hua;ZHOU Chun-bei(Chongqing Center for Disease Control and Prevention,Chongqing 400042,China)
出处
《中国病毒病杂志》
CAS
2023年第1期43-47,共5页
Chinese Journal of Viral Diseases
基金
重庆市科卫联合医学科研项目(2020FYYX234)。
关键词
猴痘
微博
大数据
数据挖掘
情绪
Monkeypox
Weibo
Big data
Data mining
Emotion
