Search (298 results, page 1 of 15)

  • × theme_ss:"Informetrie"
  1. Danell, R.: Can the quality of scientific work be predicted using information on the author's track record? (2011) 0.07
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    Abstract
    Many countries are moving towards research policies that emphasize excellence; consequently; they develop evaluation systems to identify universities, research groups, and researchers that can be said to be "excellent." Such active research policy strategies, in which evaluations are used to concentrate resources, are based on an unsubstantiated assumption that researchers' track records are indicative of their future research performance. In this study, information on authors' track records (previous publication volume and previous citation rate) is used to predict the impact of their articles. The study concludes that, to a certain degree, the impact of scientific work can be predicted using information on how often an author's previous publications have been cited. The relationship between past performance and the citation rate of articles is strongest at the high end of the citation distribution. The implications of these results are discussed in the context of a cumulative advantage process.
  2. Falkingham, L.T.; Reeves, R.: Context analysis : a technique for analysing research in a field, applied to literature on the management of R&D at the section level (1998) 0.07
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    Abstract
    Context analysis is a new method for appraising a body of publications. the process consists of creating a database of attributes assigned to each paper by the reviewer and then looking for interesting relationships in the data. Assigning the attributes requires an understanding of the subject matter of the papers. Presents findings about one particular research field, Management of R&D at the Section Level. The findings support the view that this body of academic publications does not meet the needs of practitioner R&D managers. Discusses practical aspects of how to apply the method in other fields
    Date
    22. 5.1999 19:18:46
  3. Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004) 0.06
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    Abstract
    The term author co-citation is defined and classified according to four distinct forms: the pure first-author co-citation, the pure author co-citation, the general author co-citation, and the special co-authorlco-citation. Each form can be used to obtain one count in an author co-citation study, based an a binary counting rule, which either recognizes the co-citedness of two authors in a given reference list (1) or does not (0). Most studies using author co-citations have relied solely an first-author cocitation counts as evidence of an author's oeuvre or body of work contributed to a research field. In this article, we argue that an author's contribution to a selected field of study should not be limited, but should be based an his/her complete list of publications, regardless of author ranking. We discuss the implications associated with using each co-citation form and show where simple first-author co-citations fit within our classification scheme. Examples are given to substantiate each author co-citation form defined in our classification, including a set of sample Dialog(TM) searches using references extracted from the SciSearch database.
  4. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.05
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    Date
    22. 8.2014 17:05:18
  5. Costas, R.; Leeuwen, T.N. van; Bordons, M.: Referencing patterns of individual researchers : do top scientists rely on more extensive information sources? (2012) 0.05
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    Abstract
    This study presents an analysis of the use of bibliographic references by individual scientists in three different research areas. The number and type of references that scientists include in their papers are analyzed, the relationship between the number of references and different impact-based indicators is studied from a multivariable perspective, and the referencing patterns of scientists are related to individual factors such as their age and scientific performance. Our results show inter-area differences in the number, type, and age of references. Within each area, the number of references per document increases with journal impact factor and paper length. Top-performance scientists use in their papers a higher number of references, which are more recent and more frequently covered by the Web of Science. Veteran researchers tend to rely more on older literature and non-Web of Science sources. The longer reference lists of top scientists can be explained by their tendency to publish in high impact factor journals, with stricter reference and reviewing requirements. Long reference lists suggest a broader knowledge on the current literature in a field, which is important to become a top scientist. From the perspective of the "handicap principle theory," the sustained use of a high number of references in an author's oeuvre is a costly behavior that may indicate a serious, comprehensive, and solid research capacity, but that only the best researchers can afford. Boosting papers' citations by artificially increasing the number of references does not seem a feasible strategy.
  6. Zuccala, A.; Someren, M. van; Bellen, M. van: ¬A machine-learning approach to coding book reviews as quality indicators : toward a theory of megacitation (2014) 0.05
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    Abstract
    A theory of "megacitation" is introduced and used in an experiment to demonstrate how a qualitative scholarly book review can be converted into a weighted bibliometric indicator. We employ a manual human-coding approach to classify book reviews in the field of history based on reviewers' assessments of a book author's scholarly credibility (SC) and writing style (WS). In total, 100 book reviews were selected from the American Historical Review and coded for their positive/negative valence on these two dimensions. Most were coded as positive (68% for SC and 47% for WS), and there was also a small positive correlation between SC and WS (r = 0.2). We then constructed a classifier, combining both manual design and machine learning, to categorize sentiment-based sentences in history book reviews. The machine classifier produced a matched accuracy (matched to the human coding) of approximately 75% for SC and 64% for WS. WS was found to be more difficult to classify by machine than SC because of the reviewers' use of more subtle language. With further training data, a machine-learning approach could be useful for automatically classifying a large number of history book reviews at once. Weighted megacitations can be especially valuable if they are used in conjunction with regular book/journal citations, and "libcitations" (i.e., library holding counts) for a comprehensive assessment of a book/monograph's scholarly impact.
  7. ¬Die deutsche Zeitschrift für Dokumentation, Informationswissenschaft und Informationspraxis von 1950 bis 2011 : eine vorläufige Bilanz in vier Abschnitten (2012) 0.05
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    Date
    22. 7.2012 19:35:26
    Footnote
    Besteht aus 4 Teilen: Teil 1: Eden, D., A. Arndt, A. Hoffer, T. Raschke u. P. Schön: Die Nachrichten für Dokumentation in den Jahren 1950 bis 1962 (S.159-163). Teil 2: Brose, M., E. durst, D. Nitzsche, D. Veckenstedt u. R. Wein: Statistische Untersuchung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) 1963-1975 (S.164-170). Teil 3: Bösel, J., G. Ebert, P. Garz,, M. Iwanow u. B. Russ: Methoden und Ergebnisse einer statistischen Auswertung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) 1976 bis 1988 (S.171-174). Teil 4: Engelage, H., S. Jansen, R. Mertins, K. Redel u. S. Ring: Statistische Untersuchung der Fachzeitschrift "Nachrichten für Dokumentation" (NfD) / "Information. Wissenschaft & Praxis" (IWP) 1989-2011 (S.164-170).
  8. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.04
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    Abstract
    Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
    Date
    9. 7.2006 10:22:35
  9. Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996) 0.04
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    Source
    Journal of information science. 22(1996) no.3, S.165-170
  10. Asonuma, A.; Fang, Y.; Rousseau, R.: Reflections on the age distribution of Japanese scientists (2006) 0.04
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    Date
    22. 7.2006 15:26:24
  11. Raan, A.F.J. van: Scaling rules in the science system : influence of field-specific citation characteristics on the impact of research groups (2008) 0.04
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    Date
    22. 3.2009 19:03:12
    Footnote
    Vgl. auch: Costas, R., M. Bordons u. T.N. van Leeuwen u.a.: Scaling rules in the science system: Influence of field-specific citation characteristics on the impact of individual researchers. In: Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.740-753.
  12. Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014) 0.04
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    Abstract
    Patent analysis has become important for management as it offers timely and valuable information to evaluate R&D performance and identify the prospects of patents. This study explores the scattering patterns of patent impact based on citations in 3 distinct technological areas, the liquid crystal, semiconductor, and drug technological areas, to identify the core patents in each area. The research follows the approach from Bradford's law, which equally divides total citations into 3 zones. While the result suggests that the scattering of patent citations corresponded with features of Bradford's law, the proportion of patents in the 3 zones did not match the proportion as proposed by the law. As a result, the study shows that the distributions of citations in all 3 areas were more concentrated than what Bradford's law proposed. The Groos (1967) droop was also presented by the scattering of patent citations, and the growth rate of cumulative citation decreased in the third zone.
    Date
    22. 8.2014 17:11:29
  13. Ntuli, H.; Inglesi-Lotz, R.; Chang, T.; Pouris, A.: Does research output cause economic growth or vice versa? : evidence from 34 OECD countries (2015) 0.04
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    Date
    8. 7.2015 22:00:42
  14. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.04
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    Abstract
    A recent publication in Nature reports that public R&D funding is only weakly correlated with the citation impact of a nation's articles as measured by the field-weighted citation index (FWCI; defined by Scopus). On the basis of the supplementary data, we up-scaled the design using Web of Science data for the decade 2003-2013 and OECD funding data for the corresponding decade assuming a 2-year delay (2001-2011). Using negative binomial regression analysis, we found very small coefficients, but the effects of international collaboration are positive and statistically significant, whereas the effects of government funding are negative, an order of magnitude smaller, and statistically nonsignificant (in two of three analyses). In other words, international collaboration improves the impact of research articles, whereas more government funding tends to have a small adverse effect when comparing OECD countries.
    Date
    8. 1.2019 18:22:45
  15. Hjerppe, R.: ¬An outline of bibliometrics and citation analysis (1980) 0.03
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    Type
    r
  16. Ball, R.: Wissenschaftsindikatoren im Zeitalter digitaler Wissenschaft (2007) 0.03
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    Date
    23.12.2007 19:22:21
  17. 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) 0.03
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    Date
    22. 3.2009 19:02:48
  18. Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011) 0.03
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    Date
    22. 1.2011 13:04:21
  19. Costas, R.; Zahedi, Z.; Wouters, P.: ¬The thematic orientation of publications mentioned on social media : large-scale disciplinary comparison of social media metrics with citations (2015) 0.03
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    Date
    20. 1.2015 18:30:22
  20. Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023) 0.03
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    Date
    21. 3.2023 19:22:02

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