Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal.
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| Title: | Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal. |
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| Authors: | Stringer, Michael J.1 m-stringer@northwestern.edu, Sales-Pardo, Marta2, Amaral, Luís A. Nunes3 |
| Source: | Journal of the American Society for Information Science & Technology. Jul2010, Vol. 61 Issue 7, p1377-1385. 9p. 2 Charts, 5 Graphs. |
| Subjects: | Bibliometrics, Bibliographical citations, Scientific literature, Bibliographical citation searching, Lognormal distribution, Science publishing, Information science, Online databases, Electronic information resource searching |
| Abstract: | A central issue in evaluative bibliometrics is the characterization of the citation distribution of papers in the scientific literature. Here, we perform a large-scale empirical analysis of journals from every field in Thomson Reuters' Web of Science database. We find that only 30 of the 2,184 journals have citation distributions that are inconsistent with a discrete lognormal distribution at the rejection threshold that controls the false discovery rate at 0.05. We find that large, multidisciplinary journals are over-represented in this set of 30 journals, leading us to conclude that, within a discipline, citation distributions are lognormal. Our results strongly suggest that the discrete lognormal distribution is a globally accurate model for the distribution of “eventual impact” of scientific papers published in single-discipline journal in a single year that is removed sufficiently from the present date. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of the American Society for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 51532183 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Stringer%2C+Michael+J%2E%22">Stringer, Michael J.</searchLink><relatesTo>1</relatesTo><i> m-stringer@northwestern.edu</i><br /><searchLink fieldCode="AR" term="%22Sales-Pardo%2C+Marta%22">Sales-Pardo, Marta</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Amaral%2C+Luís+A%2E+Nunes%22">Amaral, Luís A. Nunes</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+the+American+Society+for+Information+Science+%26+Technology%22">Journal of the American Society for Information Science & Technology</searchLink>. Jul2010, Vol. 61 Issue 7, p1377-1385. 9p. 2 Charts, 5 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Bibliometrics%22">Bibliometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Bibliographical+citations%22">Bibliographical citations</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+literature%22">Scientific literature</searchLink><br /><searchLink fieldCode="DE" term="%22Bibliographical+citation+searching%22">Bibliographical citation searching</searchLink><br /><searchLink fieldCode="DE" term="%22Lognormal+distribution%22">Lognormal distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Science+publishing%22">Science publishing</searchLink><br /><searchLink fieldCode="DE" term="%22Information+science%22">Information science</searchLink><br /><searchLink fieldCode="DE" term="%22Online+databases%22">Online databases</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+information+resource+searching%22">Electronic information resource searching</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A central issue in evaluative bibliometrics is the characterization of the citation distribution of papers in the scientific literature. Here, we perform a large-scale empirical analysis of journals from every field in Thomson Reuters' Web of Science database. We find that only 30 of the 2,184 journals have citation distributions that are inconsistent with a discrete lognormal distribution at the rejection threshold that controls the false discovery rate at 0.05. We find that large, multidisciplinary journals are over-represented in this set of 30 journals, leading us to conclude that, within a discipline, citation distributions are lognormal. Our results strongly suggest that the discrete lognormal distribution is a globally accurate model for the distribution of “eventual impact” of scientific papers published in single-discipline journal in a single year that is removed sufficiently from the present date. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of the American Society for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/asi.21335 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 1377 Subjects: – SubjectFull: Bibliometrics Type: general – SubjectFull: Bibliographical citations Type: general – SubjectFull: Scientific literature Type: general – SubjectFull: Bibliographical citation searching Type: general – SubjectFull: Lognormal distribution Type: general – SubjectFull: Science publishing Type: general – SubjectFull: Information science Type: general – SubjectFull: Online databases Type: general – SubjectFull: Electronic information resource searching Type: general Titles: – TitleFull: Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Stringer, Michael J. – PersonEntity: Name: NameFull: Sales-Pardo, Marta – PersonEntity: Name: NameFull: Amaral, Luís A. Nunes IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2010 Type: published Y: 2010 Identifiers: – Type: issn-print Value: 15322882 Numbering: – Type: volume Value: 61 – Type: issue Value: 7 Titles: – TitleFull: Journal of the American Society for Information Science & Technology Type: main |
| ResultId | 1 |
