%0期刊文章%@ 1438-8871 %I JMIR出版物%V 24 卡塔尔世界杯8强波胆分析%N 10 %P e40408 %T对COVID-19疫苗相关社交媒体数据进行微调情感分析:比较研究%A Melton,Chad A %A White,Brianna M %A Davis,Robert L %A Bednarczyk,Robert A %A sha - nejad，田纳西州孟菲斯市丹拉普街50号，492R，田纳西大学健康科学中心，儿科，Arash %+生物医学信息学中心，美国38103,1 9012875836，ashabann@uthsc.edu %K情感分析%K DistilRoBERTa %K自然语言处理%K社交媒体%K推特%K Reddit %K COVID-19 %K疫苗接种%K疫苗%K内容分析%K公共卫生%K监测%K错误信息%K信息流行病学%K信息质量%D 2022 %7 17.10.2022 %9原创论文%J J医学互联网Res %G英语%X背景:新型冠状病毒(COVID-19)的出现和必要的人口隔离导致寻求与大流行相关信息的新社交媒体用户数量达到前所未有的水平。目前，全球约有45亿用户，社交媒体数据为近实时分析与疾病暴发和疫苗接种有关的大量文本提供了机会。官员可以利用这些分析制定适当的公共卫生信息、数字干预措施、教育材料和政策。目的:我们的研究调查并比较了2020年1月1日至2022年3月1日期间在2个流行的社交媒体平台——reddit和twitter上表达的与COVID-19疫苗相关的公众情绪。方法:为了完成这项任务，我们创建了一个微调的DistilRoBERTa模型来预测大约950万条推文和7万条Reddit评论的情绪。为了微调我们的模型，我们的团队手动标记3600条推文的情绪，然后通过反向翻译增强我们的数据集。然后，我们使用Python编程语言和hugs Face情感分析管道进行微调模型，对每个社交媒体平台的文本情感进行分类。 Results: Our results determined that the average sentiment expressed on Twitter was more negative (5,215,830/9,518,270, 54.8%) than positive, and the sentiment expressed on Reddit was more positive (42,316/67,962, 62.3%) than negative. Although the average sentiment was found to vary between these social media platforms, both platforms displayed similar behavior related to the sentiment shared at key vaccine-related developments during the pandemic. Conclusions: Considering this similar trend in shared sentiment demonstrated across social media platforms, Twitter and Reddit continue to be valuable data sources that public health officials can use to strengthen vaccine confidence and combat misinformation. As the spread of misinformation poses a range of psychological and psychosocial risks (anxiety and fear, etc), there is an urgency in understanding the public perspective and attitude toward shared falsities. Comprehensive educational delivery systems tailored to a population’s expressed sentiments that facilitate digital literacy, health information–seeking behavior, and precision health promotion could aid in clarifying such misinformation. %M 36174192 %R 10.2196/40408 %U //www.mybigtv.com/2022/10/e40408 %U https://doi.org/10.2196/40408 %U http://www.ncbi.nlm.nih.gov/pubmed/36174192