A call for governments to pause Twitter censorship: using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion

Vanash M. Patel (), Robin Haunschild, Lutz Bornmann and George Garas
Additional contact information
Vanash M. Patel: St. Mary’s Hospital
Robin Haunschild: Max Planck Institute for Solid State Research
Lutz Bornmann: Administrative Headquarters of the Max Planck Society
George Garas: St. Mary’s Hospital

Scientometrics, 2021, vol. 126, issue 4, No 19, 3193-3207

Abstract: Abstract 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

Keywords: Altmetrics; Twitter; Spatial maps; COVID-19; SARS-CoV-2 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11192-020-03843-5

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