Research on Post-retraction Citations of COVID-19 Articles Based on Full-text Citation

Yanyu Ren, Siluo Yang

Knowledge Management Forum ›› 2023, Vol. 8 ›› Issue (5) : 399-413.

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Knowledge Management Forum ›› 2023, Vol. 8 ›› Issue (5) : 399-413. DOI: 10.13266/j.issn.2095-5472.2023.033

Research on Post-retraction Citations of COVID-19 Articles Based on Full-text Citation

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Abstract

[Purpose/Significance] During the COVID-19 pandemic, many papers on this topic were withdrawn. But it was found through authoritative databases or websites that these papers have been cited even after the retraction. This study aims to analyze the dissemination and impact of retraction at the level of citation content, and to put forward suggestions on the optimization of citation and retraction mechanisms in major public events, in order to promote the healthy development of academic exchanges. [Method/Process] Firstly, the full text of COVID-19 retraction papers and citation references were obtained from WOS, Scopus, and PubMed databases, and the citation context in the citation references was manually extracted. Then, manual annotation and content analysis were carried out through the full-text citation analysis framework consisting of four dimensions: retraction mark situation, citation object, citation position, and citation emotion. [Result/Conclusion] The probability and speed of recognition of COVID-19 retracted papers are much higher than other papers in the biomedical field, and the retracted mechanism plays a certain role in academic purification. But its content continues to spread, with unreliability and misinformation spreading widely. This phenomenon should be paid enough attention by researchers, journals and databases, and the mechanism of citation and retraction in important public events should be optimized urgently.

Key words

COVID-19 / retracted papers / full-text citation analysis / academic purification / academic impact

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Yanyu Ren , Siluo Yang. Research on Post-retraction Citations of COVID-19 Articles Based on Full-text Citation[J]. Knowledge Management Forum. 2023, 8(5): 399-413 https://doi.org/10.13266/j.issn.2095-5472.2023.033

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