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Bensman, S.J.; Leydesdorff, L.: Definition and identification of journals as bibliographic and subject entities : librarianship versus ISI Journal Citation Reports methods and their effect on citation measures (2009)
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- Abstract
- This paper explores the ISI Journal Citation Reports (JCR) bibliographic and subject structures through Library of Congress (LC) and American research libraries cataloging and classification methodology. The 2006 Science Citation Index JCR Behavioral Sciences subject category journals are used as an example. From the library perspective, the main fault of the JCR bibliographic structure is that the JCR mistakenly identifies journal title segments as journal bibliographic entities, seriously affecting journal rankings by total cites and the impact factor. In respect to JCR subject structure, the title segment, which constitutes the JCR bibliographic basis, is posited as the best bibliographic entity for the citation measurement of journal subject relationships. Through factor analysis and other methods, the JCR subject categorization of journals is tested against their LC subject headings and classification. The finding is that JCR and library journal subject analyses corroborate, clarify, and correct each other.
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Bensman, S.J.: Distributional differences of the impact factor in the sciences versus the social sciences : an analysis of the probabilistic structure of the 2005 journal citation reports (2008)
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- Abstract
- This paper examines the probability structure of the 2005 Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) Journal Citation Reports (JCR) by analyzing the Impact Factor distributions of their journals. The distribution of the SCI journals corresponded with a distribution generally modeled by the negative binomial distribution, whereas the SSCI distribution fit the Poisson distribution modeling random, rare events. Both Impact Factor distributions were positively skewed - the SCI much more so than the SSCI - indicating excess variance. One of the causes of this excess variance was that the journals highest in the Impact Factor in both JCRs tended to class in subject categories well funded by the National Institutes of Health. The main reason for the SCI Impact Factor distribution being more skewed than the SSCI one was that review journals defining disciplinary paradigms play a much more important role in the sciences than in the social sciences.
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Bensman, S.J.; Smolinsky, L.J.; Pudovkin, A.I.: Mean citation rate per article in mathematics journals : differences from the scientific model (2010)
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- Abstract
- This paper analyzes the applicability of the article mean citation rate measures in the Science Citation Index Journal Citation Reports (SCI JCR) to the five JCR mathematical subject categories. These measures are the traditional 2-year impact factor as well as the recently added 5-year impact factor and 5-year article influence score. Utilizing the 2008 SCI JCR, the paper compares the probability distributions of the measures in the mathematical categories to the probability distribution of a scientific model of impact factor distribution. The scientific model distribution is highly skewed, conforming to the negative binomial type, with much of the variance due to the important role of review articles in science. In contrast, the three article mean citation rate measures' distributions in the mathematical categories conformed to either the binomial or Poisson, indicating a high degree of randomness. Seeking reasons for this, the paper analyzes the bibliometric structure of Mathematics, finding it a disjointed discipline of isolated subfields with a weak central core of journals, reduced review function, and long cited half-life placing most citations beyond the measures' time limits. These combine to reduce the measures' variance to one commensurate with random error. However, the measures were found capable of identifying important journals. Using data from surveys of the Louisiana State University (LSU) faculty, the paper finds a higher level of consensus among mathematicians and others on which are the important mathematics journals than the measures indicate, positing that much of the apparent randomness may be due to the measures' inapplicability to mathematical disciplines. Moreover, tests of the stability of impact factor ranks across a 5-year time span suggested that the proper model for Mathematics is the negative binomial.
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Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013)
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- Date
- 17.12.2013 11:02:22
