%0期刊文章%@ 2369-2960 %I JMIR出版物%V 7% 卡塔尔世界杯8强波胆分析N 12% P e32814%推动推特上COVID-19疫苗话语流行度和病毒式传播的因素:文本挖掘与数据可视化研究%张A，王珏曼%王毅%石毅%王璐%王秀丽%+北京大学新媒体学院，北京市海淀区义和园路5号，100871，中国，86 10 6276 6689,xiuli.wang@pku.edu.cn %K COVID-19 %K疫苗%K主题建模%K LDA %K价%K分享%K病毒%K推特%K社交媒体%D 2021 %7 3.12.2021 %9原创论文%J JMIR公共卫生监测%G英文%X背景:COVID-19疫苗接种被认为是帮助结束大流行的关键预防措施。推特等社交媒体平台在有关COVID-19疫苗的公众讨论中发挥了重要作用。目的:本研究的目的是使用基于机器的文本挖掘技术，调查关于COVID-19疫苗的推文受欢迎程度和病毒式传播的消息级驱动因素。我们进一步旨在使用网络分析和可视化来检查最受欢迎和转发最多的推文的主题社区。方法:我们收集了2020年1月1日至2021年4月30日期间关于COVID-19疫苗的美国英语公开推文(N= 501531)。使用主题建模和情感分析来识别潜在的主题和效价，以及关于媒体存在、语言特征和帐户验证的自动提取信息，用于回归模型来预测点赞和转发。在2500条点赞最多的推文和2500条转发最多的推文中，采用网络分析和可视化的方法检测主题社区，并呈现主题与推文之间的关系。结果:主题建模产生了12个主题。 The regression analyses showed that 8 topics positively predicted likes and 7 topics positively predicted retweets, among which the topic of vaccine development and people’s views and that of vaccine efficacy and rollout had relatively larger effects. Network analysis and visualization revealed that the 2500 most liked and most retweeted retweets clustered around the topics of vaccine access, vaccine efficacy and rollout, vaccine development and people’s views, and vaccination status. The overall valence of the tweets was positive. Positive valence increased likes, but valence did not affect retweets. Media (photo, video, gif) presence and account verification increased likes and retweets. Linguistic features had mixed effects on likes and retweets. Conclusions: This study suggests the public interest in and demand for information about vaccine development and people’s views, and about vaccine efficacy and rollout. These topics, along with the use of media and verified accounts, have enhanced the popularity and virality of tweets. These topics could be addressed in vaccine campaigns to help the diffusion of content on Twitter. %M 34665761 %R 10.2196/32814 %U https://publichealth.www.mybigtv.com/2021/12/e32814 %U https://doi.org/10.2196/32814 %U http://www.ncbi.nlm.nih.gov/pubmed/34665761