Management School, University of Stirling, Stirling FK9 4LA, UK.
Health Promotion in Rural Areas Research Group, Gerència Territorial de la Catalunya Central, Institut Català de la Salut, 08772 Sant Fruitós de Bages, Spain.
Int J Environ Res Public Health. 2022 Apr 11;19(8):4584. doi: 10.3390/ijerph19084584.
After the first weeks of vaccination against SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. The data were retrieved from 14 March to 14 April 2021 using the keyword 'blood clots'. A dataset with = 266,677 tweets was retrieved, and a systematic random sample of 5% of tweets ( = 13,334) was entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality measure. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network comprised retweets, and the largest groups within the network were broadcast clusters in which a number of key users were retweeted. The most popular narratives involved highlighting the low risk of obtaining a blood clot from a vaccine and highlighting that a number of commonly consumed medicine have higher blood clot risks. A wide variety of users drove the discussion on Twitter, including writers, physicians, the general public, academics, celebrities, and journalists. Twitter was used to highlight the low potential of developing a blood clot from vaccines, and users on Twitter encouraged vaccinations among the public.
在接种 SARS-CoV-2 疫苗后的最初几周，有几例急性血栓形成的病例报告。这些新闻报道开始在社交媒体平台上频繁传播。本研究旨在对与整体讨论相关的 Twitter 数据进行分析。使用关键字 'blood clots'（血块），我们从 2021 年 3 月 14 日至 4 月 14 日检索了数据。检索到一个包含 = 266,677 条推文的数据集，并对 5%的推文（= 13,334）进行了系统随机抽样，输入 NodeXL 进行进一步分析。我们使用 Clauset-Newman-Moore 算法对数据进行社会网络分析。通过使用介数中心度测量来识别有影响力的用户。应用文本分析来识别此时使用的关键标签和网站。网络中超过一半的内容由转发组成，网络中最大的群组是广播群，其中许多关键用户被转发。最受欢迎的说法包括强调从疫苗中获得血栓的风险较低，以及强调许多常用药物的血栓风险更高。各种各样的用户在 Twitter 上推动了讨论，包括作家、医生、公众、学者、名人和记者。Twitter 被用来强调从疫苗中产生血栓的潜在风险低，Twitter 用户鼓励公众接种疫苗。
