Joshua M Nicholson, Ashish Uppala, Matthias Sieber, Peter Grabitz, Milo Mordaunt, Sean C Rife
{"title":"衡量维基百科中科学参考文献的质量:对超过80万篇科学文章超过1.15亿次引用的分析。","authors":"Joshua M Nicholson, Ashish Uppala, Matthias Sieber, Peter Grabitz, Milo Mordaunt, Sean C Rife","doi":"10.1111/febs.15608","DOIUrl":null,"url":null,"abstract":"<p><p>Wikipedia is a widely used online reference work which cites hundreds of thousands of scientific articles across its entries. The quality of these citations has not been previously measured, and such measurements have a bearing on the reliability and quality of the scientific portions of this reference work. Using a novel technique, a massive database of qualitatively described citations, and machine learning algorithms, we analyzed 1 923 575 Wikipedia articles which cited a total of 824 298 scientific articles in our database and found that most scientific articles cited by Wikipedia articles are uncited or untested by subsequent studies, and the remainder show a wide variability in contradicting or supporting evidence. Additionally, we analyzed 51 804 643 scientific articles from journals indexed in the Web of Science and found that similarly most were uncited or untested by subsequent studies, while the remainder show a wide variability in contradicting or supporting evidence.</p>","PeriodicalId":12261,"journal":{"name":"FEBS Journal","volume":"288 14","pages":"4242-4248"},"PeriodicalIF":5.5000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/febs.15608","citationCount":"6","resultStr":"{\"title\":\"Measuring the quality of scientific references in Wikipedia: an analysis of more than 115M citations to over 800 000 scientific articles.\",\"authors\":\"Joshua M Nicholson, Ashish Uppala, Matthias Sieber, Peter Grabitz, Milo Mordaunt, Sean C Rife\",\"doi\":\"10.1111/febs.15608\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Wikipedia is a widely used online reference work which cites hundreds of thousands of scientific articles across its entries. The quality of these citations has not been previously measured, and such measurements have a bearing on the reliability and quality of the scientific portions of this reference work. Using a novel technique, a massive database of qualitatively described citations, and machine learning algorithms, we analyzed 1 923 575 Wikipedia articles which cited a total of 824 298 scientific articles in our database and found that most scientific articles cited by Wikipedia articles are uncited or untested by subsequent studies, and the remainder show a wide variability in contradicting or supporting evidence. Additionally, we analyzed 51 804 643 scientific articles from journals indexed in the Web of Science and found that similarly most were uncited or untested by subsequent studies, while the remainder show a wide variability in contradicting or supporting evidence.</p>\",\"PeriodicalId\":12261,\"journal\":{\"name\":\"FEBS Journal\",\"volume\":\"288 14\",\"pages\":\"4242-4248\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2021-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1111/febs.15608\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"FEBS Journal\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1111/febs.15608\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/11/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"FEBS Journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1111/febs.15608","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/11/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Measuring the quality of scientific references in Wikipedia: an analysis of more than 115M citations to over 800 000 scientific articles.
Wikipedia is a widely used online reference work which cites hundreds of thousands of scientific articles across its entries. The quality of these citations has not been previously measured, and such measurements have a bearing on the reliability and quality of the scientific portions of this reference work. Using a novel technique, a massive database of qualitatively described citations, and machine learning algorithms, we analyzed 1 923 575 Wikipedia articles which cited a total of 824 298 scientific articles in our database and found that most scientific articles cited by Wikipedia articles are uncited or untested by subsequent studies, and the remainder show a wide variability in contradicting or supporting evidence. Additionally, we analyzed 51 804 643 scientific articles from journals indexed in the Web of Science and found that similarly most were uncited or untested by subsequent studies, while the remainder show a wide variability in contradicting or supporting evidence.
期刊介绍：
The FEBS Journal is an international journal devoted to the rapid publication of full-length papers covering a wide range of topics in any area of the molecular life sciences. The criteria for acceptance are originality and high quality research, which will provide novel perspectives in a specific area of research, and will be of interest to our broad readership.
The journal does not accept papers that describe the expression of specific genes and proteins or test the effect of a drug or reagent, without presenting any biological significance. Papers describing bioinformatics, modelling or structural studies of specific systems or molecules should include experimental data.
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