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Bauer, J.; Leydesdorff, L.; Bornmann, L.: Highly cited papers in Library and Information Science (LIS) : authors, institutions, and network structures (2016)
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- Abstract
- As a follow-up to the highly cited authors list published by Thomson Reuters in June 2014, we analyzed the top 1% most frequently cited papers published between 2002 and 2012 included in the Web of Science (WoS) subject category "Information Science & Library Science." In all, 798 authors contributed to 305 top 1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly cited authors by Thomson Reuters in June 2014 (http://highlycited.com/). Twelve of these 23 authors were involved in publishing 4 or more of the 305 papers under study. Analysis of coauthorship relations among the 798 highly cited scientists shows that coauthorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (a) collection and exploitation of information in clinical practices; (b) use of the Internet in public communication and commerce; and (c) scientometrics.
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Bornmann, L.: Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration? : an analysis based on data from F1000Prime and normalized citation scores (2017)
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- Abstract
- In recent years, the relationship of collaboration among scientists and the citation impact of papers have been frequently investigated. Most of the studies show that the two variables are closely related: An increasing collaboration activity (measured in terms of number of authors, number of affiliations, and number of countries) is associated with an increased citation impact. However, it is not clear whether the increased citation impact is based on the higher quality of papers that profit from more than one scientist giving expert input or other (citation-specific) factors. Thus, the current study addresses this question by using two comprehensive data sets with publications (in the biomedical area) including quality assessments by experts (F1000Prime member scores) and citation data for the publications. The study is based on more than 15,000 papers. Robust regression models are used to investigate the relationship between number of authors, number of affiliations, and number of countries, respectively, and citation impact-controlling for the papers' quality (measured by F1000Prime expert ratings). The results point out that the effect of collaboration activities on impact is largely independent of the papers' quality. The citation advantage is apparently not quality related; citation-specific factors (e.g., self-citations) seem to be important here.
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Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
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Bornmann, L.: How to analyze percentile citation impact data meaningfully in bibliometrics : the statistical analysis of distributions, percentile rank classes, and top-cited papers (2013)
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- Date
- 22. 3.2013 19:44:17
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Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Date
- 8. 1.2019 18:22:45
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Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011)
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- Date
- 22. 1.2011 12:51:07
