Patel Vanash M, Haunschild Robin, Bornmann Lutz, Garas George
Department of Surgery and Cancer, Imperial College London, 10th Floor, Queen Elizabeth the Queen Mother Wing, St. Mary's Hospital, London, W2 1NY UK.
Department of Colorectal Surgery, West Hertfordshire NHS Trust, Watford General Hospital, Vicarage Road, Watford, Hertfordshire, WD18 0HB UK.
Scientometrics. 2021;126(4):3193-3207. doi: 10.1007/s11192-020-03843-5. Epub 2021 Feb 28.
In this study we determined whether Twitter data can be used as social-spatial sensors to show how research on COVID-19/SARS-CoV-2 diffuses through the population to reach the people that are affected by the disease. We performed a cross-sectional bibliometric analysis between 23rd March and 14th April 2020. Three sources of data were used: (1) deaths per number of population for COVID-19/SARS-CoV-2 retrieved from John Hopkins University and Worldometer, (2) publications related to COVID-19/SARS-CoV-2 retrieved from World Health Organisation COVID-19 database, and (3) tweets of these publications retrieved from Altmetric.com and Twitter. In the analysis, the number of publications used was 1761, and number of tweets used was 751,068. Mapping of worldwide data illustrated that high Twitter activity was related to high numbers of COVID-19/SARS-CoV-2 deaths, with tweets inversely weighted with number of publications. Regression models of worldwide data showed a positive correlation between the national deaths per number of population and tweets when holding number of publications constant (coefficient 0.0285, S.E. 0.0003, < 0.001). Twitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 pandemic, especially to spread research with prompt public scrutiny. Governments are urged to pause censorship of social media platforms to support the scientific community's fight against COVID-19/SARS-CoV-2.
在本研究中,我们确定了推特数据是否可用作社会空间传感器,以展示关于新冠病毒/严重急性呼吸综合征冠状病毒2(COVID-19/SARS-CoV-2)的研究如何在人群中传播,从而触及受该疾病影响的人群。我们在2020年3月23日至4月14日期间进行了一项横断面文献计量分析。使用了三种数据来源:(1)从约翰·霍普金斯大学和世界ometers网站获取的每人口COVID-19/SARS-CoV-2死亡人数,(2)从世界卫生组织COVID-19数据库获取的与COVID-19/SARS-CoV-2相关的出版物,以及(3)从Altmetric.com和推特获取的这些出版物的推文。在分析中,使用的出版物数量为1761篇,使用的推文数量为751,068条。全球数据映射表明,推特的高活跃度与大量的COVID-19/SARS-CoV-2死亡人数相关,推文与出版物数量呈反比加权。全球数据的回归模型显示,在出版物数量保持不变的情况下,每人口国家死亡人数与推文之间存在正相关(系数0.0285,标准误差0.0003,<0.001)。在COVID-19/SARS-CoV-2大流行期间,推特在快速的研究响应中可以发挥关键作用,特别是在迅速接受公众审查的情况下传播研究成果。敦促各国政府暂停对社交媒体平台的审查,以支持科学界抗击COVID-19/SARS-CoV-2。