Search (39 results, page 2 of 2)

  • × language_ss:"e"
  • × theme_ss:"Informetrie"
  • × year_i:[2000 TO 2010}
  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. Raan, A.F.J. van: Scaling rules in the science system : influence of field-specific citation characteristics on the impact of research groups (2008) 0.01
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    Date
    22. 3.2009 19:03:12
  8. Leydesdorff, L.; Sun, Y.: National and international dimensions of the Triple Helix in Japan : university-industry-government versus international coauthorship relations (2009) 0.01
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    Date
    22. 3.2009 19:07:20
  9. He, Z.-L.: International collaboration does not have greater epistemic authority (2009) 0.01
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    Date
    26. 9.2009 11:22:05
  10. Raan, A.F.J. van; Noyons, E.C.M.: Discovery of patterns of scientific and technological development and knowledge transfer (2002) 0.01
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    Source
    Gaining insight from research information (CRIS2002): Proceedings of the 6th International Conference an Current Research Information Systems, University of Kassel, August 29 - 31, 2002. Eds: W. Adamczak u. A. Nase
  11. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.01
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    Date
    22. 7.2006 16:11:05
  12. Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007) 0.01
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    Abstract
    Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.
  13. Meho, L.I.; Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers : a comparison of Scopus and Web of Science (2008) 0.01
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    Abstract
    This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR - a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially when citations in conference proceedings are sought, and that researchers should manually calculate h scores instead of relying on system calculations.
  14. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.01
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    Date
    22. 3.2009 17:52:50
  15. Mukherjee, B.: Do open-access journals in library and information science have any scholarly impact? : a bibliometric study of selected open-access journals using Google Scholar (2009) 0.01
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    Date
    22. 3.2009 17:54:59
  16. Costas, R.; Bordons, M.; Leeuwen, T.N. van; Raan, A.F.J. van: Scaling rules in the science system : Influence of field-specific citation characteristics on the impact of individual researchers (2009) 0.01
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    Date
    22. 3.2009 19:02:48
  17. Stock, W.G.; Weber, S.: Facets of informetrics : Preface (2006) 0.01
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    Abstract
    According to Jean M. Tague-Sutcliffe "informetrics" is "the study of the quantitative aspects of information in any form, not just records or bibliographies, and in any social group, not just scientists" (Tague-Sutcliffe, 1992, 1). Leo Egghe also defines "informetrics" in a very broad sense. "(W)e will use the term' informetrics' as the broad term comprising all-metrics studies related to information science, including bibliometrics (bibliographies, libraries,...), scientometrics (science policy, citation analysis, research evaluation,...), webometrics (metrics of the web, the Internet or other social networks such as citation or collaboration networks), ..." (Egghe, 2005b,1311). According to Concepcion S. Wilson "informetrics" is "the quantitative study of collections of moderatesized units of potentially informative text, directed to the scientific understanding of information processes at the social level" (Wilson, 1999, 211). We should add to Wilson's units of text also digital collections of images, videos, spoken documents and music. Dietmar Wolfram divides "informetrics" into two aspects, "system-based characteristics that arise from the documentary content of IR systems and how they are indexed, and usage-based characteristics that arise how users interact with system content and the system interfaces that provide access to the content" (Wolfram, 2003, 6). We would like to follow Tague-Sutcliffe, Egghe, Wilson and Wolfram (and others, for example Björneborn & Ingwersen, 2004) and call this broad research of empirical information science "informetrics". Informetrics includes therefore all quantitative studies in information science. If a scientist performs scientific investigations empirically, e.g. on information users' behavior, on scientific impact of academic journals, on the development of the patent application activity of a company, on links of Web pages, on the temporal distribution of blog postings discussing a given topic, on availability, recall and precision of retrieval systems, on usability of Web sites, and so on, he or she contributes to informetrics. We see three subject areas in information science in which such quantitative research takes place, - information users and information usage, - evaluation of information systems, - information itself, Following Wolfram's article, we divide his system-based characteristics into the "information itself "-category and the "information system"-category. Figure 1 is a simplistic graph of subjects and research areas of informetrics as an empirical information science.
  18. Tonta, Y.; Ünal, Y.: Scatter of journals and literature obsolescence reflected in document delivery requests (2005) 0.01
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    Date
    20. 3.2005 10:54:22
  19. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.01
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    Date
    9. 7.2006 10:22:35