Search (156 results, page 1 of 8)

  • × year_i:[2000 TO 2010}
  • × theme_ss:"Informetrie"
  1. Nicolaisen, J.: Citation analysis (2007) 0.06
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    Date
    13. 7.2008 19:53:22
  2. H-Index auch im Web of Science (2008) 0.03
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    Content
    "Zur Kurzmitteilung "Latest enhancements in Scopus: ... h-Index incorporated in Scopus" in den letzten Online-Mitteilungen (Online-Mitteilungen 92, S.31) ist zu korrigieren, dass der h-Index sehr wohl bereits im Web of Science enthalten ist. Allerdings findet man/frau diese Information nicht in der "cited ref search", sondern neben der Trefferliste einer Quick Search, General Search oder einer Suche über den Author Finder in der rechten Navigationsleiste unter dem Titel "Citation Report". Der "Citation Report" bietet für die in der jeweiligen Trefferliste angezeigten Arbeiten: - Die Gesamtzahl der Zitierungen aller Arbeiten in der Trefferliste - Die mittlere Zitationshäufigkeit dieser Arbeiten - Die Anzahl der Zitierungen der einzelnen Arbeiten, aufgeschlüsselt nach Publikationsjahr der zitierenden Arbeiten - Die mittlere Zitationshäufigkeit dieser Arbeiten pro Jahr - Den h-Index (ein h-Index von x sagt aus, dass x Arbeiten der Trefferliste mehr als x-mal zitiert wurden; er ist gegenüber sehr hohen Zitierungen einzelner Arbeiten unempfindlicher als die mittlere Zitationshäufigkeit)."
    Date
    6. 4.2008 19:04:22
    Object
    H-Index
    Source
    Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 61(2008) H.1, S.124-125
  3. Wettlauf der Wissenschaft (2004) 0.03
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    Footnote
    Vgl.: http://www.i-med.ac.at/mypoint/news/2004051201.xml (cf) (Quelle: U.S. Is Losing Its Dominance In the Sciences, by WI LLIAM J. BROAD, New York Times, May 3, 2004)
    Source
    Online Mitteilungen. 2004, Nr.79, S.22-23 [=Mitteilungen VÖB 57(2004) H.2]
  4. Kim, P.J.; Lee, J.Y.; Park, J.-H.: Developing a new collection-evaluation method : mapping and the user-side h-index (2009) 0.02
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    Abstract
    This study proposes a new visualization method and index for collection evaluation. Specifically, it develops a network-based mapping technique and a user-focused Hirsch index (user-side h-index) given the lack of previous studies on collection evaluation methods that have used the h-index. A user-side h-index is developed and compared with previous indices (use factor, difference of percentages, collection-side h-index) that represent the strengths of the subject classes of a library collection. The mapping procedure includes the subject-usage profiling of 63 subject classes and collection-usage map generations through the pathfinder network algorithm. Cluster analyses are then conducted upon the pathfinder network to generate 5 large and 14 small clusters. The nodes represent the strengths of the subject-class usages reflected by the user-side h-index. The user-side h-index was found to have advantages (e.g., better demonstrating the real utility of each subject class) over the other indices. It also can more clearly distinguish the strengths between the subject classes than can collection-side h-index. These results may help to identify actual usage and strengths of subject classes in library collections through visualized maps. This may be a useful rationale for the establishment of the collection-development plan.
    Object
    h-index
  5. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.02
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    Date
    4.12.2006 12:12:22
    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.401-406
  6. Rostaing, H.; Barts, N.; Léveillé, V.: Bibliometrics: representation instrument of the multidisciplinary positioning of a scientific area : Implementation for an Advisory Scientific Committee (2007) 0.02
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    Date
    30.12.2007 11:22:39
  7. Egghe, L.: Empirical and combinatorial study of country occurrences in multi-authored papers (2006) 0.02
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    Abstract
    Papers written by several authors can be classified according to the countries of the author affiliations. The empirical part of this paper consists of two datasets. One dataset consists of 1,035 papers retrieved via the search "pedagog*" in the years 2004 and 2005 (up to October) in Academic Search Elite which is a case where phi(m) = the number of papers with m =1, 2,3 ... authors is decreasing, hence most of the papers have a low number of authors. Here we find that #, m = the number of times a country occurs j times in a m-authored paper, j =1, ..., m-1 is decreasing and that # m, m is much higher than all the other #j, m values. The other dataset consists of 3,271 papers retrieved via the search "enzyme" in the year 2005 (up to October) in the same database which is a case of a non-decreasing phi(m): most papers have 3 or 4 authors and we even find many papers with a much higher number of authors. In this case we show again that # m, m is much higher than the other #j, m values but that #j, m is not decreasing anymore in j =1, ..., m-1, although #1, m is (apart from # m, m) the largest number amongst the #j,m. The combinatorial part gives a proof of the fact that #j,m decreases for j = 1, m-1, supposing that all cases are equally possible. This shows that the first dataset is more conform with this model than the second dataset. Explanations for these findings are given. From the data we also find the (we think: new) distribution of number of papers with n =1, 2,3,... countries (i.e. where there are n different countries involved amongst the m (a n) authors of a paper): a fast decreasing function e.g. as a power law with a very large Lotka exponent.
    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.427-432
  8. 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) 0.02
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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.
    Object
    h-index
  9. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.02
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    Date
    26.12.2007 19:22:05
  10. Antonakis, J.; Lalive, R.: Quantifying scholarly impact : IQp versus the Hirsch h (2008) 0.02
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    Abstract
    Hirsch's (2005) h index of scholarly output has generated substantial interest and wide acceptance because of its apparent ability to quantify scholarly impact simply and accurately. We show that the excitement surrounding h is premature for three reasons: h stagnates with increasing scientific age; it is highly dependent on publication quantity; and it is highly dependent on field-specific citation rates. Thus, it is not useful for comparing scholars across disciplines. We propose the scholarly index of quality and productivity (IQp) as an alternative to h. The new index takes into account a scholar's total impact and also corrects for field-specific citation rates, scholarly productivity, and scientific age. The IQp accurately predicts group membership on a common metric, as tested on a sample of 80 scholars from three populations: (a) Nobel winners in physics (n = 10), chemistry (n = 10), medicine (n = 10), and economics (n = 10), and towering psychologists (n = 10); and scholars who have made more modest contributions to science including randomly selected (b) fellows (n = 15) and (c) members (n = 15) of the Society of Industrial and Organizational Psychology. The IQp also correlates better with expert ratings of greatness than does the h index.
  11. Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009) 0.02
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    Abstract
    This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors.
  12. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.02
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    Date
    3. 1.2007 17:22:03
  13. Cheng, S.; YunTao, P.; JunPeng, Y.; Hong, G.; ZhengLu, Y.; ZhiYu, H.: PageRank, HITS and impact factor for journal ranking (2009) 0.02
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    Abstract
    Journal citation measures are one of the most widely used bibliometric tools. The most well-known measure is the ISI Impact Factor, under the standard definition, the impact factor of journal j in a given year is the average number of citations received by papers published in the previous two years of journal j. However, the impact factor has its "intrinsic" limitations, it is a ranking measure based fundamentally on a pure counting of the in-degrees of nodes in the network, and its calculation does not take into account the "impact" or "prestige" of the journals in which the citations appear. Google's PageRank algorithm and Kleinberg's HITS method are webpage ranking algorithm, they compute the scores of webpages based on a combination of the number of hyperlinks that point to the page and the status of pages that the hyperlinks originate from, a page is important if it is pointed to by other important pages. We demonstrate how popular webpage algorithm PageRank and HITS can be used ranking journal, and we compared ISI impact factor, PageRank and HITS for journal ranking, and with PageRank and HITS compute respectively including self-citation and non self-citation, and discussed the merit and shortcomings and the scope of application that the various algorithms are used to rank journal.
  14. Schlögl, C.; Gorraiz, J.; Bart, C.; Bargmann, M.: Messen und gemessen werden : Möglichkeiten und Grenzen quantitativer Forschungsevaluierungen am Beispiel eines Institutsvergleichs (2001) 0.02
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    Source
    nfd Information - Wissenschaft und Praxis. 52(2001) H.4, S.221-228
  15. Gorraiz, J.; Schlögl, C.: Zusammenhang von Zeitschriftennachfrage und -zitationshäufigkeiten : ¬Eine bibliometrische Analyse eines Dokumentlieferdienstes am Beispiel von Subito (2003) 0.02
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    Source
    Zeitschrift für Bibliothekswesen und Bibliographie. 50(2003) H.3, S.131-140
  16. Bar-Ilan, J.: Informetrics (2009) 0.02
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    Abstract
    Informetrics is a subfield of information science and it encompasses bibliometrics, scientometrics, cybermetrics, and webometrics. This encyclopedia entry provides an overview of informetrics and its subfields. In general, informetrics deals with quantitative aspects of information: its production, dissemination, evaluation, and use. Bibliometrics and scientometrics study scientific literature: papers, journals, patents, and citations; while in webometric studies the sources studied are Web pages and Web sites, and citations are replaced by hypertext links. The entry introduces major topics in informetrics: citation analysis and citation related studies, the journal impact factor, the recently defined h-index, citation databases, co-citation analysis, open access publications and its implications, informetric laws, techniques for mapping and visualization of informetric phenomena, the emerging subfields of webometrics, cybermetrics and link analysis, and research evaluation.
  17. Ball, R.: Wissenschaftsindikatoren im Zeitalter digitaler Wissenschaft (2007) 0.02
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    Date
    23.12.2007 19:22:21
    Source
    B.I.T.online. 10(2007) H.2, S.xxx-xxx
  18. Hayer, L.: Lazarsfeld zitiert : eine bibliometrische Analyse (2008) 0.02
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    Date
    22. 6.2008 12:54:12
    Source
    Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 61(2008) H.2, S.14-20
  19. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.01
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    Date
    22. 7.2006 15:22:28
  20. Johan Bollen, J.; Van de Sompel, H.: Usage impact factor : the effects of sample characteristics on usage-based impact metrics (2008) 0.01
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