论文标题

计算机科学缩回论文的分析

An analysis of retracted papers in Computer Science

论文作者

Shepperd, Martin, Yousefi, Leila

论文摘要

背景:无论出于何种原因,研究论文的撤回都是一种日益增长的现象。但是,尽管撤回的纸张信息可通过出版商公开获取,但它在某种程度上分布和不一致。目的:目的是评估:(i)计算机科学研究(CS)缩回研究的程度和性质(ii)撤回作品的撤退后引文行为以及(iii)对系统评价和映射研究的潜在影响。方法:我们分析了回缩观察数据库,并从科学和Google Scholar网络中获取引文信息。结果:我们发现回收观察数据库中的33,955个条目(2022年5月16日),2,816个分类为CS,即约8.3%。对于CS,有56%的缩回论文几乎没有或根本没有有关原因的信息。这与其他学科的26%形成鲜明对比。不同的发行商之间也存在显着差异,多种版本的缩回纸的趋势超出了记录版本(VOR),并且在正式撤回纸张后很长一段时间内引用了新的引用。结论:不幸的是,撤回似乎是一份科学论文的足够共同的结果,我们作为一个研究社区需要更加认真地对其进行认真对待,例如,出版商之间的标准化程序和分类法以及提供适当的研究工具。最后,我们建议在进行二次分析和荟萃分析时特别谨慎,这些分析和荟萃分析有可能受到这些问题主要研究污染的风险。

Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact on systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., approximately 8.3%. For CS, 56% of retracted papers, provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also a remarkable disparity between different publishers, a tendency for multiple versions of a retracted paper over and above the Version of Record (VoR), and for new citations long after a paper is officially retracted. Conclusions: Unfortunately retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies.

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