Search (31 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Informetrie"
  • × year_i:[2000 TO 2010}
  1. Craven, T.C.: Determining authorship of Web pages (2006) 0.05
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    Abstract
    Assignability of authors to Web pages using either normal browsing procedures or browsing assisted by simple automatic extraction was investigated. Candidate strings for 1000 pages were extracted automatically from title elements, meta-tags, and address-like and copyright-like passages; 539 of the pages produced at least one candidate: 310 candidates from titles, 66 from meta-tags, 91 from address-like passages, and 259 from copyright-like passages. An assistant attempted to identify personal authors for 943 pages by examining the pages themselves and related pages; this added 90 pages with authors to the pages from which no candidate strings were extracted. Specific problems are noted and some refinements to the extraction methods are suggested.
  2. Abt, H.A.; Garfield, E.: Is the relationship between numbers of references and paper lengths the same for all sciences? (2002) 0.04
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    Abstract
    It has been shown in the physical sciences that a paper's length is related to its number of references in a linear manner. Abt and Garfield here look at the life and social sciences with the thought that if the relation holds the citation counts will provide a measure of relative importance across these disciplines. In the life sciences 200 research papers from 1999-2000 were scanned in each of 10 journals to produce counts of 1000 word normalized pages. In the social sciences an average of 70 research papers in nine journals were scanned for the two-year period. Papers of average length in the various sciences have the same average number of references within plus or minus 17%. A look at the 30 to 60 papers over the two years in 18 review journals indicates twice the references of research papers of the same length.
  3. Janssens, F.; Leta, J.; Glänzel, W.; Moor, B. de: Towards mapping library and information science (2006) 0.04
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    Abstract
    In an earlier study by the authors, full-text analysis and traditional bibliometric methods were combined to map research papers published in the journal Scientometrics. The main objective was to develop appropriate techniques of full-text analysis and to improve the efficiency of the individual methods in the mapping of science. The number of papers was, however, rather limited. In the present study, we extend the quantitative linguistic part of the previous studies to a set of five journals representing the field of Library and Information Science (LIS). Almost 1000 articles and notes published in the period 2002-2004 have been selected for this exercise. The optimum solution for clustering LIS is found for six clusters. The combination of different mapping techniques, applied to the full text of scientific publications, results in a characteristic tripod pattern. Besides two clusters in bibliometrics, one cluster in information retrieval and one containing general issues, webometrics and patent studies are identified as small but emerging clusters within LIS. The study is concluded with the analysis of cluster representations by the selected journals.
  4. Yoshikane, F.; Kageura, K.; Tsuji, K.: ¬A method for the comparative analysis of concentration of author productivity, giving consideration to the effect of sample size dependency of statistical measures (2003) 0.03
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    Abstract
    Studies of the concentration of author productivity based upon counts of papers by individual authors will produce measures that change systematically with sample size. Yoshikane, Kageura, and Tsuji seek a statistical framework which will avoid this scale effect problem. Using the number of authors in a field as an absolute concentration measure, and Gini's index as a relative concentration measure, they describe four literatures form both viewpoints with measures insensitive to one another. Both measures will increase with sample size. They then plot profiles of the two measures on the basis of a Monte-Carlo simulation of 1000 trials for 20 equally spaced intervals and compare the characteristics of the literatures. Using data from conferences hosted by four academic societies between 1992 and 1997, they find a coefficient of loss exceeding 0.15 indicating measures will depend highly on sample size. The simulation shows that a larger sample size leads to lower absolute concentration and higher relative concentration. Comparisons made at the same sample size present quite different results than the original data and allow direct comparison of population characteristics.
  5. Nicolaisen, J.: Citation analysis (2007) 0.03
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    Date
    13. 7.2008 19:53:22
  6. 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
  7. Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005) 0.02
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    Date
    20. 1.2007 17:02:22
  8. Raan, A.F.J. van: Statistical properties of bibliometric indicators : research group indicator distributions and correlations (2006) 0.01
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    Date
    22. 7.2006 16:20:22
  9. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01
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    Date
    22. 3.2009 19:22:35
  10. Rostaing, H.; Barts, N.; Léveillé, V.: Bibliometrics: representation instrument of the multidisciplinary positioning of a scientific area : Implementation for an Advisory Scientific Committee (2007) 0.01
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    Date
    30.12.2007 11:22:39
  11. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.01
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    Abstract
    Collaboration is a major research policy objective, but does it deliver higher quality research? This study uses citation analysis to examine the Web of Science (WoS) Information Science & Library Science subject category (IS&LS) to ascertain whether, in general, more highly cited articles are more highly collaborative than other articles. It consists of two investigations. The first investigation is a longitudinal comparison of the degree and proportion of collaboration in five strata of citation; it found that collaboration in the highest four citation strata (all in the most highly cited 22%) increased in unison over time, whereas collaboration in the lowest citation strata (un-cited articles) remained low and stable. Given that over 40% of the articles were un-cited, it seems important to take into account the differences found between un-cited articles and relatively highly cited articles when investigating collaboration in IS&LS. The second investigation compares collaboration for 35 influential information scientists; it found that their more highly cited articles on average were not more highly collaborative than their less highly cited articles. In summary, although collaborative research is conducive to high citation in general, collaboration has apparently not tended to be essential to the success of current and former elite information scientists.
    Date
    22. 3.2009 12:43:51
  12. Burrell, Q.L.: Predicting future citation behavior (2003) 0.01
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    Date
    29. 3.2003 19:22:48
  13. Leydesdorff, L.: Can networks of journal-journal citations be used as indicators of change in the social sciences? (2003) 0.01
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    Date
    6.11.2005 19:02:22
  14. Asonuma, A.; Fang, Y.; Rousseau, R.: Reflections on the age distribution of Japanese scientists (2006) 0.01
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    Date
    22. 7.2006 15:26:24
  15. Haycock, L.A.: Citation analysis of education dissertations for collection development (2004) 0.01
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    Date
    10. 9.2000 17:38:22
  16. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.01
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    Date
    3. 1.2007 17:22:03
  17. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.01
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    Date
    26.12.2007 19:22:05
  18. Althouse, B.M.; West, J.D.; Bergstrom, C.T.; Bergstrom, T.: Differences in impact factor across fields and over time (2009) 0.01
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    Date
    23. 2.2009 18:22:28
  19. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.01
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    Date
    22. 3.2009 17:49:11
  20. Camacho-Miñano, M.-del-Mar; Núñez-Nickel, M.: ¬The multilayered nature of reference selection (2009) 0.01
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    Date
    22. 3.2009 19:05:07