Search (65 results, page 1 of 4)

  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.05 
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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
  2. 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
  3. Song, M.; Kim, S.Y.; Zhang, G.; Ding, Y.; Chambers, T.: Productivity and influence in bioinformatics : a bibliometric analysis using PubMed central (2014) 0.01 
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    Abstract
    Bioinformatics is a fast-growing field based on the optimal use of "big data" gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in-depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full-text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co-evolving with other biomedical disciplines.
  4. Zhao, R.; Wu, S.: ¬The network pattern of journal knowledge transfer in library and information science in China (2014) 0.01 
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    Abstract
    Using the library and information science journals 2003-2012 in Nanjing University's Chinese Social Sciences Citation Index as data sources, the paper reveals the citation structure implied in these journals by applying social network analysis. Results show that, first, journal knowledge transfer activity in library and information science is frequent, and both the level of knowledge and discipline integration as well as the knowledge gap influenced knowledge transfer activity. According to the out-degree and in-degree, journals can be divided into three kinds. Second, based on professional bias and citation frequency, the knowledge transfer network can be divided into four blocks. With the change of discipline capacity and knowledge gap among journals, the "core-periphery" structure of the knowledge transfer network is getting weaker. Finally, regions of the knowledge transfer network evolved from a "weak-weak" subgroup to a "strong-weak" subgroup or a "weak-strong" subgroup, and then move to a "strong-strong" subgroup.
  5. Albarrán, P.; Perianes-Rodríguez, A.; Ruiz-Castillo, J.: Differences in citation impact across countries (2015) 0.01 
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    Abstract
    Using a large data set, indexed by Thomson Reuters, consisting of 4.4 million articles published in 1998-2003 with a 5-year citation window for each year, this article studies country citation distributions for a partitioning of the world into 36 countries and two geographical areas in eight broad scientific fields and the all-sciences case. The two key findings are the following. First, country citation distributions are highly skewed and very similar to each other in all fields. Second, to a large extent, differences in country citation distributions can be accounted for by scale factors. The Empirical situation described in the article helps to understand why international comparisons of citation impact according to (a) mean citations and (b) the percentage of articles in each country belonging to the top 10% of the most cited articles are so similar to each other.
  6. Zhou, Q.; Leydesdorff, L.: ¬The normalization of occurrence and co-occurrence matrices in bibliometrics using Cosine similarities and Ochiai coefficients (2016) 0.01 
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    Abstract
    We prove that Ochiai similarity of the co-occurrence matrix is equal to cosine similarity in the underlying occurrence matrix. Neither the cosine nor the Pearson correlation should be used for the normalization of co-occurrence matrices because the similarity is then normalized twice, and therefore overestimated; the Ochiai coefficient can be used instead. Results are shown using a small matrix (5 cases, 4 variables) for didactic reasons, and also Ahlgren et?al.'s (2003) co-occurrence matrix of 24 authors in library and information sciences. The overestimation is shown numerically and will be illustrated using multidimensional scaling and cluster dendograms. If the occurrence matrix is not available (such as in internet research or author cocitation analysis) using Ochiai for the normalization is preferable to using the cosine.
  7. Scholarly metrics under the microscope : from citation analysis to academic auditing (2015) 0.01 
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    Date
    22. 1.2017 17:12:50
  8. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01 
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    Date
    22. 8.2014 17:05:18
  9. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.01 
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    Date
    20. 1.2019 11:22:31
  10. An, L.; Zhang, J.; Yu, C.: ¬The visual subject analysis of library and information science journals with self-organizing map (2011) 0.01 
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    Abstract
    Academic journals play an important role in scientific communication. The effective organization of journals can help reveal the thematic contents of journals and thus make them more user-friendly. In this study, the Self-Organizing Map (SOM) technique was employed to visually analyze the 60 library and information science-related journals published from 2006 to 2008. The U-matrix by Ultsch (2003) was applied to categorize the journals into 19 clusters according to their subjects. Four journals were recommended to supplement library collections although they were not indexed by SCI/SSCI. A novel SOM display named Attribute Accumulation Matrix (AA-matrix) was proposed, and the results from this method show that they correlate significantly with the total occurrences of the subjects in the investigated journals. The AA-matrix was employed to identify the 86 salient subjects, which could be manually classified into 7 meaningful groups. A method of the Salient Attribute Projection was constructed to label the attribute characteristics of different clusters. Finally, the subject characteristics of the journals with high impact factors (IFs) were also addressed. The findings of this study can lead to a better understanding of the subject structure and characteristics of library/information-related journals.
  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. Costas, R.; Zahedi, Z.; Wouters, P.: Do "altmetrics" correlate with citations? : extensive comparison of altmetric indicators with citations from a multidisciplinary perspective (2015) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2003-2019
  13. Bornmann, L.: How much does the expected number of citations for a publication change if it contains the address of a specific scientific institute? : a new approach for the analysis of citation data on the institutional level based on regression models (2016) 0.01 
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    Abstract
    Citation data for institutes are generally provided as numbers of citations or as relative citation rates (as, for example, in the Leiden Ranking). These numbers can then be compared between the institutes. This study aims to present a new approach for the evaluation of citation data at the institutional level, based on regression models. As example data, the study includes all articles and reviews from the Web of Science for the publication year 2003 (n?=?886,416 papers). The study is based on an in-house database of the Max Planck Society. The study investigates how much the expected number of citations for a publication changes if it contains the address of an institute. The calculation of the expected values allows, on the one hand, investigating how the citation impact of the papers of an institute appears in comparison with the total of all papers. On the other hand, the expected values for several institutes can be compared with one another or with a set of randomly selected publications. Besides the institutes, the regression models include factors which can be assumed to have a general influence on citation counts (e.g., the number of authors).
  14. Perianes-Rodriguez, A.; Ruiz-Castillo, J.: University citation distributions (2016) 0.01 
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    Abstract
    We investigate the citation distributions of the 500 universities in the 2013 edition of the Leiden Ranking produced by The Centre for Science and Technological Studies. We use a Web of Science data set consisting of 3.6 million articles published in 2003 to 2008 and classified into 5,119 clusters. The main findings are the following. First, the universality claim, according to which all university-citation distributions, appropriately normalized, follow a single functional form, is not supported by the data. Second, the 500 university citation distributions are all highly skewed and very similar. Broadly speaking, university citation distributions appear to behave as if they differ by a relatively constant scale factor over a large, intermediate part of their support. Third, citation-impact differences between universities account for 3.85% of overall citation inequality. This percentage is greatly reduced when university citation distributions are normalized using their mean normalized citation scores (MNCSs) as normalization factors. Finally, regarding practical consequences, we only need a single explanatory model for the type of high skewness characterizing all university citation distributions, and the similarity of university citation distributions goes a long way in explaining the similarity of the university rankings obtained with the MNCS and the Top 10% indicator.
  15. Thelwall, M.; Kousha, K.: SlideShare presentations, citations, users, and trends : a professional site with academic and educational uses (2017) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.8, S.1989-2003
  16. 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.
  17. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.01 
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    Date
    26.10.2014 20:22:22
  18. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.01 
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