Can tweets be used to detect problems early with scientific papers? A case study of three retracted COVID-19/SARS-CoV-2 papers

Author:

Haunschild RobinORCID,Bornmann Lutz

Abstract

AbstractMethodological mistakes, data errors, and scientific misconduct are considered prevalent problems in science that are often difficult to detect. In this study, we explore the potential of using data from Twitter for discovering problems with publications. In this case study, we analyzed tweet texts of three retracted publications about COVID-19 (Coronavirus disease 2019)/SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and their retraction notices. We did not find early warning signs in tweet texts regarding one publication, but we did find tweets that casted doubt on the validity of the two other publications shortly after their publication date. An extension of our current work might lead to an early warning system that makes the scientific community aware of problems with certain publications. Other sources, such as blogs or post-publication peer-review sites, could be included in such an early warning system. The methodology proposed in this case study should be validated using larger publication sets that also include a control group, i.e., publications that were not retracted.

Funder

Max Planck Institute for Solid State Research

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Science Applications,General Social Sciences

Reference57 articles.

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4. Bae, S., Kim, M.-C., Kim, J. Y., Cha, H.-H., Lim, J. S., Jung, J., Kim, M.-J., Oh, D. Y., Lee, M.-K., Choi, S.-H., Sung, M., Hong, S.-B., Chung, J.-W., & Kim, S.-H. (2020). Effectiveness of surgical and cotton masks in blocking SARS–CoV-2: A controlled comparison in 4 patients. Annals of Internal Medicine, 173(1), W22–W23. https://doi.org/10.7326/M20-1342.

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