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  • × theme_ss:"Informetrie"
  1. Pierce, S.J.: Boundary crossing in research literatures as a means of interdisciplinary information transfer (1999) 0.11 
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    Abstract
    Contemporary models of interdisciplinary information transfer treat disciplines as such sharply bounded groups that boundary-crossing publication (contributions to disciplinary literatures authored by researchers from other disciplines) should be very difficult, if not impossible. Yet boundary-crossing authors can be identified in many disciplinary literatures. A study of 4 core journals in political science and sociology identified 199 articles between 1971 and 1990. Two-thirds of these articles had single authors, and only one in six had coauthors from the discipline of the journal in which they were published. Readership and use of these articles, as measured by citation rates, was only slightly below normal. The articles were judged successful in interdisciplinary information transfer in that they received more citation sfrom the disciplines with which their first authors were affiliated, and more citations from other disciplines than from either the discipline of publication or the first author's discipline. Results suggest that disciplinary boundaries are less restricitive than the literature suggests, and that boundary-crossing publications are involved in complex patterns of interdisciplinary information transfer
  2. Bensman, S.J.: Garfield and the impact factors (2007) 0.10 
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  3. Bensman, S.J.: Probability distributions in library and information science : a historical and practitioner viewpoint (2000) 0.05 
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  4. Bensman, S.J.; Smolinsky, L.J.: Lotka's inverse square law of scientific productivity : its methods and statistics (2017) 0.04 
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  5. 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) 0.04 
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  6. 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) 0.04 
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  7. Williams, C.J.; O'Rourke, M.; Eigenbrode, S.D.; O'Loughlin, I.; Crowley, S.J.: Using bibliometrics to support the facilitation of cross-disciplinary communication (2013) 0.03 
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  8. Nicholls, P.T.: Empirical validation of Lotka's law (1986) 0.03 
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    Source
    Information processing and management. 22(1986), S.417-419
  9. Nicolaisen, J.: Citation analysis (2007) 0.03 
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    Date
    13. 7.2008 19:53:22
  10. Fiala, J.: Information flood : fiction and reality (1987) 0.03 
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    Source
    Thermochimica acta. 110(1987), S.11-22
  11. Ahlgren, P.; Järvelin, K.: Measuring impact of twelve information scientists using the DCI index (2010) 0.03 
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    Abstract
    The Discounted Cumulated Impact (DCI) index has recently been proposed for research evaluation. In the present work an earlier dataset by Cronin and Meho (2007) is reanalyzed, with the aim of exemplifying the salient features of the DCI index. We apply the index on, and compare our results to, the outcomes of the Cronin-Meho (2007) study. Both authors and their top publications are used as units of analysis, which suggests that, by adjusting the parameters of evaluation according to the needs of research evaluation, the DCI index delivers data on an author's (or publication's) lifetime impact or current impact at the time of evaluation on an author's (or publication's) capability of inviting citations from highly cited later publications as an indication of impact, and on the relative impact across a set of authors (or publications) over their lifetime or currently.
  12. Danell, R.: Can the quality of scientific work be predicted using information on the author's track record? (2011) 0.03 
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    Abstract
    Many countries are moving towards research policies that emphasize excellence; consequently; they develop evaluation systems to identify universities, research groups, and researchers that can be said to be "excellent." Such active research policy strategies, in which evaluations are used to concentrate resources, are based on an unsubstantiated assumption that researchers' track records are indicative of their future research performance. In this study, information on authors' track records (previous publication volume and previous citation rate) is used to predict the impact of their articles. The study concludes that, to a certain degree, the impact of scientific work can be predicted using information on how often an author's previous publications have been cited. The relationship between past performance and the citation rate of articles is strongest at the high end of the citation distribution. The implications of these results are discussed in the context of a cumulative advantage process.
  13. Bensman, S.J.: Urquhart's and Garfield's laws : the British controversy over their validity (2001) 0.02 
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  14. Bensman, S.J.; Smolinsky, L.J.; Pudovkin, A.I.: Mean citation rate per article in mathematics journals : differences from the scientific model (2010) 0.02 
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  15. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.02 
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    Date
    22. 5.1999 19:22:35
  16. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.02 
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    Date
    22. 7.2006 15:22:28
  17. Diodato, V.: Dictionary of bibliometrics (1994) 0.02 
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
  18. Bookstein, A.: Informetric distributions : I. Unified overview (1990) 0.02 
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    Date
    22. 7.2006 18:55:29
  19. Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990) 0.02 
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    Date
    22. 7.2006 18:55:55
  20. Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004) 0.02 
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    Abstract
    The term author co-citation is defined and classified according to four distinct forms: the pure first-author co-citation, the pure author co-citation, the general author co-citation, and the special co-authorlco-citation. Each form can be used to obtain one count in an author co-citation study, based an a binary counting rule, which either recognizes the co-citedness of two authors in a given reference list (1) or does not (0). Most studies using author co-citations have relied solely an first-author cocitation counts as evidence of an author's oeuvre or body of work contributed to a research field. In this article, we argue that an author's contribution to a selected field of study should not be limited, but should be based an his/her complete list of publications, regardless of author ranking. We discuss the implications associated with using each co-citation form and show where simple first-author co-citations fit within our classification scheme. Examples are given to substantiate each author co-citation form defined in our classification, including a set of sample Dialog(TM) searches using references extracted from the SciSearch database.

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