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  • × theme_ss:"Informetrie"
  1. Bohlin, L.; Esquivel, A.V.; Lancichinetti, A.; Rosvall, M.: Robustness of journal rankings by network flows with different amounts of memory (2016) 0.06 
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    Abstract
    As the number of scientific journals has multiplied, journal rankings have become increasingly important for scientific decisions. From submissions and subscriptions to grants and hirings, researchers, policy makers, and funding agencies make important decisions influenced by journal rankings such as the ISI journal impact factor. Typically, the rankings are derived from the citation network between a selection of journals and unavoidably depend on this selection. However, little is known about how robust rankings are to the selection of included journals. We compare the robustness of three journal rankings based on network flows induced on citation networks. They model pathways of researchers navigating the scholarly literature, stepping between journals and remembering their previous steps to different degrees: zero-step memory as impact factor, one-step memory as Eigenfactor, and two-step memory, corresponding to zero-, first-, and second-order Markov models of citation flow between journals. We conclude that higher-order Markov models perform better and are more robust to the selection of journals. Whereas our analysis indicates that higher-order models perform better, the performance gain for higher-order Markov models comes at the cost of requiring more citation data over a longer time period.
  2. Wang, P.: ¬An empirical study of knowledge structures of research topics (1999) 0.03 
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    Abstract
    How knowledge is organized in human memory is of interest to both information science and cognitive science. The current information retrieval (IR) systems can be improved if we understand which conceptual structures could facilitate users in information processing and seeking. This project examined twenty-two cognitive maps on ten research topics generated by ten experts and eleven non-experts. Experts were those who had completed a research project on the topic prior to participating in this study, while non-experts were from the same academic department who were familiar with the topic but had not conducted any in-depth research on it. A research topic can be represented by a vocabulary and the relationships among the terms in the vocabulary. A cognitive map visualizes the vocabulary and its configuration in a plane. We observed that experts did not generate the maps much faster than non-experts. Both experts and non-experts modified the given vocabulary by either adding or dropping terms. The dominant configuration for the maps was top-down, while five maps were orientated in left-right or radical structure (from a center). Experts tended to use problem-oriented approach to organize the vocabulary while non-experts often applied discipline-oriented hierarchical structure. Despite of many differences in vocabulary and structure by individuals, there are terms clustered in a similar ways across maps indicating an agreed-upon semantic closeness among these terms
  3. Waltman, L.; Eck, N.J. van: ¬A new methodology for constructing a publication-level classification system of science : keyword maps in Google scholar citations (2012) 0.03 
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    Abstract
    Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification systems have two important limitations: They offer only a limited amount of detail, and they have difficulties with multidisciplinary journals. To avoid these limitations, we introduce a new methodology for constructing classification systems at the level of individual publications. In the proposed methodology, publications are clustered into research areas based on citation relations. The methodology is able to deal with very large numbers of publications. We present an application in which a classification system is produced that includes almost 10 million publications. Based on an extensive analysis of this classification system, we discuss the strengths and the limitations of the proposed methodology. Important strengths are the transparency and relative simplicity of the methodology and its fairly modest computing and memory requirements. The main limitation of the methodology is its exclusive reliance on direct citation relations between publications. The accuracy of the methodology can probably be increased by also taking into account other types of relations-for instance, based on bibliographic coupling.
  4. 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
  5. Nicolaisen, J.: Citation analysis (2007) 0.03 
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    Date
    13. 7.2008 19:53:22
  6. Fiala, J.: Information flood : fiction and reality (1987) 0.03 
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    Source
    Thermochimica acta. 110(1987), S.11-22
  7. 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
  8. 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
  9. 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)
  10. Bookstein, A.: Informetric distributions : I. Unified overview (1990) 0.02 
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    Date
    22. 7.2006 18:55:29
  11. Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990) 0.02 
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    Date
    22. 7.2006 18:55:55
  12. 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
  13. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.02 
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    Date
    18. 3.2014 19:13:22
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. Chongde, W.; Zhe, W.: Evaluation of the models for Bradford's law (1998) 0.01 
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    Date
    22. 5.1999 19:12:28
  20. Tijssen, R.J.W.; Wijk, E. van: ¬The global science base of information and communication technologies : bibliometric analysis of ICT research papers (1998) 0.01 
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    Date
    22. 5.1999 19:26:54

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