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, p < 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.

在这项研究中，我们确定 Twitter 数据是否可以用作社交空间传感器，以展示对 COVID-19/SARS-CoV-2 的研究如何通过人群传播到受疾病影响的人群。我们在 2020 年 3 月 23 日至 4 月 14 日期间进行了横断面文献计量分析。使用了三个数据来源：（1）从约翰霍普金斯大学和 Worldometer 检索到的 COVID-19/SARS-CoV-2 的每人口死亡人数，（ 2) 从世界卫生组织 COVID-19 数据库中检索到的与 COVID-19/SARS-CoV-2 相关的出版物，以及 (3) 从 Altmetric.com 和 Twitter 中检索到的这些出版物的推文。在分析中，使用的出版物数量为 1761 条，使用的推文数量为 751,068 条。全球数据的映射表明，推特的高活动与大量 COVID-19/SARS-CoV-2 死亡有关，推文与出版物的数量成反比。全球数据的回归模型显示，当出版物数量保持不变（系数 0.0285、SE 0.0003、p  < 0.001)。Twitter 可以在 COVID-19/SARS-CoV-2 大流行期间的快速研究响应中发挥关键作用，尤其是在迅速进行公众监督的情况下传播研究。敦促各国政府暂停对社交媒体平台的审查，以支持科学界与 COVID-19/SARS-CoV-2 的斗争。