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：

---

可以使用推文通过科学论文尽早发现问题吗？以三篇收回的COVID-19 / SARS-CoV-2论文为例。

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，通常很难发现。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，我们分析了三篇关于COVID-19（2019年冠状病毒病）/ SARS-CoV-2（严重急性呼吸系统综合症冠状病毒2）的撤回出版物的鸣叫文本及其撤回通知。我们没有在有关某出版物的推文中找到预警信号，但我们确实发现了推文，对其他两种出版物在其出版日期之后的有效性产生了怀疑。我们当前工作的扩展可能会导致建立一个预警系统，使科学界意识到某些出版物的问题。其他来源 例如博客或发布后的同行评审站点，可以包含在这样的预警系统中。本案例研究中提出的方法应使用较大的出版物集（包括对照组）进行验证，即未撤回的出版物。