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  1. Nicolaisen, J.: Citation analysis (2007) 0.05
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    Date
    13. 7.2008 19:53:22
  2. Fiala, J.: Information flood : fiction and reality (1987) 0.05
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    Source
    Thermochimica acta. 110(1987), S.11-22
  3. Huang, H.; Andrews, J.; Tang, J.: Citation characterization and impact normalization in bioinformatics journals (2012) 0.04
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  4. Kulczycki, E.; Huang, Y.; Zuccala, A.A.; Engels, T.C.E.; Ferrara, A.; Guns, R.; Pölönen, J.; Sivertsen, G.; Taskin, Z.; Zhang, L.: Uses of the Journal Impact Factor in national journal rankings in China and Europe (2022) 0.03
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  5. 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) 0.02
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    Date
    22. 8.2014 17:11:29
  6. Frandsen, T.F.; Nicolaisen, J.: ¬The ripple effect : citation chain reactions of a nobel prize (2013) 0.02
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    Abstract
    This paper explores the possible citation chain reactions of a Nobel Prize using the mathematician Robert J. Aumann as a case example. The results show that the award of the Nobel Prize in 2005 affected not only the citations to his work, but also affected the citations to the references in his scientific oeuvre. The results indicate that the spillover effect is almost as powerful as the effect itself. We are consequently able to document a ripple effect in which the awarding of the Nobel Prize ignites a citation chain reaction to Aumann's scientific oeuvre and to the references in its nearest citation network. The effect is discussed using innovation decision process theory as a point of departure to identify the factors that created a bandwagon effect leading to the reported observations.
    Date
    22. 3.2013 16:21:09
  7. King, J.: ¬A review of bibliometric and other indicators and their role in research evaluation (1987) 0.02
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  8. Williams, J.; Clark, J.D.: ¬The information explosion : fact or myth? (1992) 0.02
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  9. Kurtz, M.; Bollen, J.: Usage bibliometrics (2010) 0.02
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  10. Lancaster, F.W.; Li, J.: ¬The law of constant accessibility of information (1988/89) 0.02
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  11. Nicolaisen, J.: ¬The J-shaped distribution of citedness (2002) 0.02
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    Abstract
    A new approach for investigating the correlation between research quality and citation counts is presented and applied to a case study of the relationship between peer evaluations reflected in scholarly book reviews and the citation frequencies of reviewed books. Results of the study designate a J-shaped distribution between the considered variables, presumably caused by a skewed allocation of negative citations. The paper concludes with suggestions for further research.
  12. Kreider, J.: ¬The correlation of local citation data with citation data from Journal Citation Reports (1999) 0.02
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    Date
    10. 9.2000 17:38:22
  13. 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
  14. Albarrán, P.; Ruiz-Castillo, J.: References made and citations received by scientific articles (2011) 0.02
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    Abstract
    This article studies massive evidence about references made and citations received after a 5-year citation window by 3.7 million articles published in 1998 to 2002 in 22 scientific fields. We find that the distributions of references made and citations received share a number of basic features across sciences. Reference distributions are rather skewed to the right while citation distributions are even more highly skewed: The mean is about 20 percentage points to the right of the median, and articles with a remarkable or an outstanding number of citations represent about 9% of the total. Moreover, the existence of a power law representing the upper tail of citation distributions cannot be rejected in 17 fields whose articles represent 74.7% of the total. Contrary to the evidence in other contexts, the value of the scale parameter is above 3.5 in 13 of the 17 cases. Finally, power laws are typically small, but capture a considerable proportion of the total citations received.
  15. Hicks, D.; Wang, J.: Coverage and overlap of the new social sciences and humanities journal lists (2011) 0.02
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    Date
    22. 1.2011 13:21:28
  16. Li, J.; Shi, D.: Sleeping beauties in genius work : when were they awakened? (2016) 0.02
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    Date
    22. 1.2016 14:13:32
  17. 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) 0.02
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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.
  18. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.02
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    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  19. Chen, C.-M.: Classification of scientific networks using aggregated journal-journal citation relations in the Journal Citation Reports (2008) 0.02
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    Abstract
    I propose an approach to classifying scientific networks in terms of aggregated journal-journal citation relations of the ISI Journal Citation Reports using the affinity propagation method. This algorithm is applied to obtain the classification of SCI and SSCI journals by minimizing intracategory journal-journal (J-J) distances in the database, where distance between journals is calculated from the similarity of their annual citation patterns with a cutoff parameter, t, to restrain the maximal J-J distance. As demonstrated in the classification of SCI journals, classification of scientific networks with different resolution is possible by choosing proper values of t. Twenty journal categories in SCI are found to be stable despite a difference of an order of magnitude in t. In our classifications, the level of specificity of a category can be found by looking at its value of RJ (the average distance of members of a category to its representative journal), and relatedness of category members is implied by the value of DJ-J (the average DJ-J distance within a category). Our results are consistent with the ISI classification scheme, and the level of relatedness for most categories in our classification is higher than their counterpart in the ISI classification scheme.
  20. 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.

Years

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