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Yan, E.: Finding knowledge paths among scientific disciplines (2014)
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- Date
- 26.10.2014 20:22:22
-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
-
Campanario, J.M.: Large increases and decreases in journal impact factors in only one year : the effect of journal self-citations (2011)
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- Date
- 22. 1.2011 12:53:00
-
Ding, Y.: Applying weighted PageRank to author citation networks (2011)
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- Date
- 22. 1.2011 13:02:21
-
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)
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- Date
- 18. 3.2014 18:22:21
-
Onodera, N.; Iwasawa, M.; Midorikawa, N.; Yoshikane, F.; Amano, K.; Ootani, Y.; Kodama, T.; Kiyama, Y.; Tsunoda, H.; Yamazaki, S.: ¬A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search (2011)
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-
Peng, T.-Q.; Zhu, J.J.H.: Where you publish matters most : a multilevel analysis of factors affecting citations of internet studies (2012)
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-
Ye, F.Y.; Leydesdorff, L.: ¬The "academic trace" of the performance matrix : a mathematical synthesis of the h-index and the integrated impact indicator (I3) (2014)
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- Abstract
- The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.
-
Li, R.; Chambers, T.; Ding, Y.; Zhang, G.; Meng, L.: Patent citation analysis : calculating science linkage based on citing motivation (2014)
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Kenyon, T.: Defining and measuring research impact in the humanities, social sciences and creative arts in the digital age (2014)
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McKeown, K.; Daume III, H.; Chaturvedi, S.; Paparrizos, J.; Thadani, K.; Barrio, P.; Biran, O.; Bothe, S.; Collins, M.; Fleischmann, K.R.; Gravano, L.; Jha, R.; King, B.; McInerney, K.; Moon, T.; Neelakantan, A.; O'Seaghdha, D.; Radev, D.; Templeton, C.; Teufel, S.: Predicting the impact of scientific concepts using full-text features (2016)
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-
Mutz, R.; Wolbring, T.; Daniel, H.-D.: ¬The effect of the "very important paper" (VIP) designation in Angewandte Chemie International Edition on citation impact : a propensity score matching analysis (2017)
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Farys, R.; Wolbring, T.: Matched control groups for modeling events in citation data : an illustration of nobel prize effects in citation networks (2017)
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Shuai, X.; Rollins, J.; Moulinier, I.; Custis, T.; Edmunds, M.; Schilder, F.: ¬A multidimensional investigation of the effects of publication retraction on scholarly impact (2017)
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Franssen, T.; Wouters, P.: Science and its significant other : representing the humanities in bibliometric scholarship (2019)
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-
Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010)
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- Date
- 28. 9.2010 12:54:22
-
Albarrán, P.; Ruiz-Castillo, J.: References made and citations received by scientific articles (2011)
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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.
-
D'Angelo, C.A.; Giuffrida, C.; Abramo, G.: ¬A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments (2011)
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- Date
- 22. 1.2011 13:06:52
-
Hicks, D.; Wang, J.: Coverage and overlap of the new social sciences and humanities journal lists (2011)
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- Date
- 22. 1.2011 13:21:28
-
Frandsen, T.F.; Nicolaisen, J.: ¬The ripple effect : citation chain reactions of a nobel prize (2013)
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- Date
- 22. 3.2013 16:21:09
