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  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. Yan, E.: Disciplinary knowledge production and diffusion in science (2016) 0.01 
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    Abstract
    This study examines patterns of dynamic disciplinary knowledge production and diffusion. It uses a citation data set of Scopus-indexed journals and proceedings. The journal-level citation data set is aggregated into 27 subject areas and these subjects are selected as the unit of analysis. A 3-step approach is employed: the first step examines disciplines' citation characteristics through scientific trading dimensions; the second step analyzes citation flows between pairs of disciplines; and the third step uses egocentric citation networks to assess individual disciplines' citation flow diversity through Shannon entropy. The results show that measured by scientific impact, the subjects of Chemical Engineering, Energy, and Environmental Science have the fastest growth. Furthermore, most subjects are carrying out more diversified knowledge trading practices by importing higher volumes of knowledge from a greater number of subjects. The study also finds that the growth rates of disciplinary citations align with the growth rates of global research and development (R&D) expenditures, thus providing evidence to support the impact of R&D expenditures on knowledge production.
  2. Zhang, L.; Rousseau, R.; Glänzel, W.: Document-type country profiles (2011) 0.01 
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  3. Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014) 0.01 
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  4. Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014) 0.01 
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    Abstract
    This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
  5. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.01 
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    Date
    26.10.2014 20:22:22
  6. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.01 
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    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  7. Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011) 0.01 
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    Date
    22. 1.2011 12:53:00
  8. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01 
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    Date
    22. 1.2011 13:02:21
  9. Schlögl, C.: Internationale Sichtbarkeit der europäischen und insbesondere der deutschsprachigen Informationswissenschaft (2013) 0.01 
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    Date
    22. 3.2013 14:04:09
  10. Vieira, E.S.; Cabral, J.A.S.; Gomes, J.A.N.F.: Definition of a model based on bibliometric indicators for assessing applicants to academic positions (2014) 0.01 
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    Date
    18. 3.2014 18:22:21
  11. Shelton, R.D.; Leydesdorff, L.: Publish or patent : bibliometric evidence for empirical trade-offs in national funding strategies (2012) 0.01 
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    Abstract
    Multivariate linear regression models suggest a trade-off in allocations of national research and development (R&D). Government funding and spending in the higher education sector encourage publications as a long-term research benefit. Conversely, other components such as industrial funding and spending in the business sector encourage patenting. Our results help explain why the United States trails the European Union in publications: The focus in the United States is on industrial funding-some 70% of its total R&D investment. Likewise, our results also help explain why the European Union trails the United States in patenting, since its focus on government funding is less effective than industrial funding in predicting triadic patenting. Government funding contributes negatively to patenting in a multiple regression, and this relationship is significant in the case of triadic patenting. We provide new forecasts about the relationships of the United States, the European Union, and China for publishing; these results suggest much later dates for changes than previous forecasts because Chinese growth has been slowing down since 2003. Models for individual countries might be more successful than regression models whose parameters are averaged over a set of countries because nations can be expected to differ historically in terms of the institutional arrangements and funding schemes.
  12. Schreiber, M.: Inconsistencies of recently proposed citation impact indicators and how to avoid them (2012) 0.01 
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    Abstract
    It is shown that under certain circumstances in particular for small data sets, the recently proposed citation impact indicators I3(6PR) and R(6,k) behave inconsistently when additional papers or citations are taken into consideration. Three simple examples are presented, in which the indicators fluctuate strongly and the ranking of scientists in the evaluated group is sometimes completely mixed up by minor changes in the database. The erratic behavior is traced to the specific way in which weights are attributed to the six percentile rank classes, specifically for the tied papers. For 100 percentile rank classes, the effects will be less serious. For the six classes, it is demonstrated that a different way of assigning weights avoids these problems, although the nonlinearity of the weights for the different percentile rank classes can still lead to (much less frequent) changes in the ranking. This behavior is not undesired because it can be used to correct for differences in citation behavior in different fields. Remaining deviations from the theoretical value R(6,k) = 1.91 can be avoided by a new scoring rule: the fractional scoring. Previously proposed consistency criteria are amended by another property of strict independence at which a performance indicator should aim.
  13. Rousseau, R.; Egghe, L.; Guns, R.: Becoming metric-wise : a bibliometric guide for researchers (2018) 0.01 
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  14. Egghe, L.; Rousseau, R.: ¬The Hirsch index of a shifted Lotka function and its relation with the impact factor (2012) 0.01 
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  15. 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) 0.01 
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  16. Egghe, L.: Remarks on the paper by A. De Visscher, "what does the g-index really measure?" (2012) 0.01 
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    Abstract
    The author presents a different view on properties of impact measures than given in the paper of De Visscher (2011). He argues that a good impact measure works better when citations are concentrated rather than spread out over articles. The author also presents theoretical evidence that the g-index and the R-index can be close to the square root of the total number of citations, whereas this is not the case for the A-index. Here the author confirms an assertion of De Visscher.
  17. Tartanus, M.; Wnuk, A.; Kozak, M.; Hartley, J.: Graphs and prestige in agricultural journals (2013) 0.01 
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    Abstract
    In this article, we report on the status of graphs in 21 scientific agricultural journals indexed in Thomson Reuters' Web of Knowledge. We analyze the authors' use of graphs in this context in relation to the quality of these journals as measured by their 2-year impact factors. We note a substantial variability in the use of graphs in this context: For one journal, 100% of the papers include graphs, whereas for others only about 50% of them include graphs. We also show that higher impact agricultural journals publish more papers with graphs and that there are more graphs in these papers than in those in journals with lower impact factors (r = +0.40).
  18. Hovden, R.: Bibliometrics for Internet media : applying the h-index to YouTube (2013) 0.01 
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  19. Bornmann, L.: How well does a university perform in comparison with its peers? : The use of odds, and odds ratios, for the comparison of institutional citation impact using the Leiden Rankings (2015) 0.01 
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    Editor
    Mutz, R.
  20. Liu, Y.; Rousseau, R.: Towards a representation of diffusion and interaction of scientific ideas : the case of fiber optics communication (2012) 0.01 
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