Methodological 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.

中文翻译：

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推文可以用于早期发现科学论文的问题吗？三篇被撤回的 COVID-19/SARS-CoV-2 论文的案例研究。

方法错误、数据错误和科学不端行为被认为是科学中普遍存在的问题，通常难以发现。在这项研究中，我们探索了使用 Twitter 数据发现出版物问题的潜力。在本案例研究中，我们分析了关于 COVID-19（2019 年冠状病毒病）/SARS-CoV-2（严重急性呼吸综合征冠状病毒 2）的三篇撤回出版物的推文文本及其撤回通知。我们没有在关于一个出版物的推文文本中发现预警信号，但我们确实发现了在发布日期后不久对另外两个出版物的有效性产生怀疑的推文。我们当前工作的扩展可能会导致早期预警系统，使科学界意识到某些出版物的问题。其他来源，例如博客或发表后的同行评审网站，可以包含在这种早期预警系统中。本案例研究中提出的方法应使用更大的出版物集进行验证，该出版物集还包括一个对照组，即未撤回的出版物。