An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006.
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| Title: | An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006. |
|---|---|
| Authors: | Ruimin Ma1, Qiangbin Dai1, Chaoqun Ni1, Xuelu Li1 |
| Source: | Scientometrics. Oct2009, Vol. 81 Issue 1, p33-46. 14p. |
| Subjects: | Citation analysis, Bibliographic coupling, Co-citation coupling, Google Inc., Search engines, Research in information science, Social network research, Factor analysis, Computer network resources |
| Geographic Terms: | China |
| Abstract: | Author co-citation analysis (ACA) is an important method for discovering the intellectual structure of a given scientific field. Since traditional ACA was confined to ISI Web of Knowledge (WoK), the co-citation counts of pairs of authors mainly depended on the data indexed in WoK. Fortunately, Google Scholar has integrated different academic databases from different publishers, providing an opportunity of conducting ACA in a wider range. In this paper, we conduct ACA of information science in China with the Chinese Google Scholar. Firstly, a brief introduction of Chinese Google Scholar is made, including retrieval principles and data formats. Secondly, the methods used in our paper are given. Thirdly, 31 most important authors of information science in China are selected as research objects. In the part of empirical study, factor analysis is used to find the main research directions of information science in China. Pajek, a powerful tool in social network analysis, is employed to visualize the author co-citation matrix as well. Finally, the resemblances and the differences between China and other countries in information science are pointed out. [ABSTRACT FROM AUTHOR] |
| Copyright of Scientometrics is the property of Springer Nature 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 44837836 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ruimin+Ma%22">Ruimin Ma</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Qiangbin+Dai%22">Qiangbin Dai</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chaoqun+Ni%22">Chaoqun Ni</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Xuelu+Li%22">Xuelu Li</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Scientometrics%22">Scientometrics</searchLink>. Oct2009, Vol. 81 Issue 1, p33-46. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Citation+analysis%22">Citation analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Bibliographic+coupling%22">Bibliographic coupling</searchLink><br /><searchLink fieldCode="DE" term="%22Co-citation+coupling%22">Co-citation coupling</searchLink><br /><searchLink fieldCode="DE" term="%22Google+Inc%2E%22">Google Inc.</searchLink><br /><searchLink fieldCode="DE" term="%22Search+engines%22">Search engines</searchLink><br /><searchLink fieldCode="DE" term="%22Research+in+information+science%22">Research in information science</searchLink><br /><searchLink fieldCode="DE" term="%22Social+network+research%22">Social network research</searchLink><br /><searchLink fieldCode="DE" term="%22Factor+analysis%22">Factor analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+resources%22">Computer network resources</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Author co-citation analysis (ACA) is an important method for discovering the intellectual structure of a given scientific field. Since traditional ACA was confined to ISI Web of Knowledge (WoK), the co-citation counts of pairs of authors mainly depended on the data indexed in WoK. Fortunately, Google Scholar has integrated different academic databases from different publishers, providing an opportunity of conducting ACA in a wider range. In this paper, we conduct ACA of information science in China with the Chinese Google Scholar. Firstly, a brief introduction of Chinese Google Scholar is made, including retrieval principles and data formats. Secondly, the methods used in our paper are given. Thirdly, 31 most important authors of information science in China are selected as research objects. In the part of empirical study, factor analysis is used to find the main research directions of information science in China. Pajek, a powerful tool in social network analysis, is employed to visualize the author co-citation matrix as well. Finally, the resemblances and the differences between China and other countries in information science are pointed out. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Scientometrics is the property of Springer Nature 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: 10.1007/s11192-009-2063-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 33 Subjects: – SubjectFull: Citation analysis Type: general – SubjectFull: Bibliographic coupling Type: general – SubjectFull: Co-citation coupling Type: general – SubjectFull: Google Inc. Type: general – SubjectFull: Search engines Type: general – SubjectFull: Research in information science Type: general – SubjectFull: Social network research Type: general – SubjectFull: Factor analysis Type: general – SubjectFull: Computer network resources Type: general – SubjectFull: China Type: general Titles: – TitleFull: An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ruimin Ma – PersonEntity: Name: NameFull: Qiangbin Dai – PersonEntity: Name: NameFull: Chaoqun Ni – PersonEntity: Name: NameFull: Xuelu Li IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 01389130 Numbering: – Type: volume Value: 81 – Type: issue Value: 1 Titles: – TitleFull: Scientometrics Type: main |
| ResultId | 1 |
