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

  1. Vanash M. Patel
  2. Robin Haunschild
  3. Lutz Bornmann
  4. George Garas

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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  < 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.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.27.20114983: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    On one hand, New York state became the global epicentre of the pandemic after the virus spread through Europe, and over a third of USA COVID-19/SARSCoV-2 deaths have occurred in New York state, with the majority in New York City.(13) On the other hand, the USA is the most prolific publisher of high-quality science in the world, but the top-performing institutes are concentrated in Massachusetts, California and Maryland.(33) Before concluding, it is important to consider the limitations of this study. We have analysed tweets mentioning publications in a quantitative manner which does not account for the association of the tweet with the publication (i.e. a tweet may reference a valid study but claim it to be ‘fake news’ or have another negative overtone). We have not performed any thematic analysis of the tweets in terms of their content (e.g., are tweets referring to testing for COVID-19/SARS-CoV-2, therapies, or vaccines), quality (e.g., whether tweets are referring to randomised controlled trials or letters), or who tweeted these (e.g., individual researchers, members of the public, universities or pharmaceutical industries). Moreover, no distinction was made between tweets and retweets (of original tweets), which raises the question whether a different handling of retweets could yield different results. These are interesting questions which might be an interesting topic of further research. Despite these limitations, our study has a number of strengths. We have used an evi...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1007/s11192-020-03843-5
  3. Version published to 10.1101/2020.05.27.20114983 on medRxiv