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  • × theme_ss:"Informetrie"
  1. Wagner-Döbler, R.: Kognitive Mobilität und Zipfs "Principle of Least Effort" (2004) 0.02 
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    Abstract
    Unter kognitiver Mobilität verstehe ich im folgenden nicht die Mobilität von Information, sondern die Bewegung des Denkens, und zwar hier des wissenschaftlichen Denkens. Wissenschaftliches Denken vollzieht sich disziplinär sowie interdisziplinär, im informationellen Austausch von Disziplinen und Forschungsgebieten. Dieser Austausch unterliegt, wie die Wissenschaftsgeschichte lehrt, einer Entwicklungsdynamik, die als Abfolge von Wanderungen oder Übergängen zwischen Forschungsgebieten in folgendem Sinn verständen werden kann. Beschäftigt sich ein Forscher A zum Zeitpunkt t1 mit Forschungsgebiet X und zum Zeitpunkt t2 als nächstes mit Forschungsgebiet Y, so liegt ein Übergang von X nach Y vor. Gibt es für diese Art von Übergängen charakteristische Eigenschaften oder Regularitäten.> Ein wichtiges Merkmal solcher Übergänge ist der Grad der Verwandtschaft, der kognitiven Affinität zwischen Ausgangs- und Zielgebiet der Migration. Am Beispiel der rund 150.000 Migrationen zwischen den mathematischen Subdisziplinen, wie sie sich in den Zeitschriftenartikel-Nachweisen der Mathematical Reviews von 1959 bis 1975 widerspiegeln, wurde das Verhältnis von kognitiver Mobilität und Affinität empirisch systematisch untersucht. Es bestätigte sich George K. Zipfs "Principle of Least Effort". Zählreiche Mechanismen und Faustregeln der Wissensorganisation dürften der Wirksamkeit dieses Prinzips zugrundeliegen.
  2. Ye, F.Y.; Leydesdorff, L.: ¬The "academic trace" of the performance matrix : a mathematical synthesis of the h-index and the integrated impact indicator (I3) (2014) 0.02 
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    Abstract
    The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.
  3. Jiang, X.; Zhu, X.; Chen, J.: Main path analysis on cyclic citation networks (2020) 0.02 
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  4. Boutin, E.: ¬La recherche d'information sur Internet au prisme de la théorie des facettes (2008) 0.02 
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    Type
    x
  5. Hu, X.; Rousseau, R.; Chen, J.: ¬A new approach for measuring the value of patents based on structural indicators for ego patent citation networks (2012) 0.02 
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  6. Egghe, L.: ¬A noninformetric analysis of the relationship between citation age and journal productivity (2001) 0.01 
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    Abstract
    A problem, raised by Wallace (JASIS, 37,136-145,1986), on the relation between the journal's median citation age and its number of articles is studied. Leaving open the problem as such, we give a statistical explanation of this relationship, when replacing "median" by "mean" in Wallace's problem. The cloud of points, found by Wallace, is explained in this sense that the points are scattered over the area in first quadrant, limited by a curve of the form y=1 + E/x**2 where E is a constant. This curve is obtained by using the Central Limit Theorem in statistics and, hence, has no intrinsic informetric foundation. The article closes with some reflections on explanations of regularities in informetrics, based on statistical, probabilistic or informetric results, or on a combination thereof
  7. Huang, X.; Peng, F,; An, A.; Schuurmans, D.: Dynamic Web log session identification with statistical language models (2004) 0.01 
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  8. Lin, X.; White, H.D.; Buzydlowski, J.: Real-time author co-citation mapping for online searching (2003) 0.01 
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  9. Egghe, L.: Influence of adding or deleting items and sources on the h-index (2010) 0.01 
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    Abstract
    Adding or deleting items such as self-citations has an influence on the h-index of an author. This influence will be proved mathematically in this article. We hereby prove the experimental finding in E. Gianoli and M.A. Molina-Montenegro ([2009]) that the influence of adding or deleting self-citations on the h-index is greater for low values of the h-index. Why this is logical also is shown by a simple theoretical example. Adding or deleting sources such as adding or deleting minor contributions of an author also has an influence on the h-index of this author; this influence is modeled in this article. This model explains some practical examples found in X. Hu, R. Rousseau, and J. Chen (in press).
  10. Zhou, P.; Su, X.; Leydesdorff, L.: ¬A comparative study on communication structures of Chinese journals in the social sciences (2010) 0.01 
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  11. Koulouri, X.; Ifrim, C.; Wallace, M.; Pop, F.: Making sense of citations (2017) 0.01 
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  12. Zheng, X.; Sun, A.: Collecting event-related tweets from twitter stream (2019) 0.01 
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  13. Hu, X.; Rousseau, R.: Do citation chimeras exist? : The case of under-cited influential articles suffering delayed recognition (2019) 0.01 
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  14. Tay, W.; Zhang, X.; Karimi , S.: Beyond mean rating : probabilistic aggregation of star ratings based on helpfulness (2020) 0.01 
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  15. Liu, X.; Bu, Y.; Li, M.; Li, J.: Monodisciplinary collaboration disrupts science more than multidisciplinary collaboration (2024) 0.01 
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  16. 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
  17. 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
  18. Li, T.-C.: Reference sources in periodicals : research note (1995) 0.01 
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    Abstract
    Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
  19. Pichappan, P.; Sangaranachiyar, S.: Ageing approach to scientific eponyms (1996) 0.01 
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    Footnote
    Report presented at the 16th National Indian Association of Special Libraries and Information Centres Seminar Special Interest Group Meeting on Informatrics in Bombay, 19-22 Dec 94
  20. Mommoh, O.M.: Subject analysis of post-graduate theses in library, archival and information science at Ahmadu Bello University, Zaria (1995/96) 0.01 
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    Source
    Library focus. 13/14(1995/96), S.22-25

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