-
Järvelin, K.; Persson, O.: ¬The DCI-index : discounted cumulated impact-based research evaluation (2008)
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- Abstract
- The article by K. Järvelin & O. Persson published in JASIST 59(9), The DCI-Index: Discounted Cumulated Impact-Based Research Evaluation, (pp. 1433-1440) contains an unfortunate error in one of its formulas, Equation 3. The present paper gives the correction and an example of impact analysis based on the corrected formula.
-
Egghe, L.; Rousseau, R.: Introduction to informetrics : quantitative methods in library, documentation and information science (1990)
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- Classification
- BCGS (FH K)
- GHBS
- BCGS (FH K)
-
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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-
Newby, G.B.; Greenberg, J.; Jones, P.: Open source software development and Lotka's law : bibliometric patterns in programming (2003)
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- Abstract
- Newby, Greenberg, and Jones analyze programming productivity of open source software by counting registered developers contributions found in the Linux Software Map and in Scourceforge. Using seven years of data from a subset of the Linux directory tree LSM data provided 4503 files with 3341 unique author names. The distribution follows Lotka's Law with an exponent of 2.82 as verified by the Kolmolgorov-Smirnov one sample goodness of fit test. Scourceforge data is broken into developers and administrators, but when both were used as authors the Lotka distribution exponent of 2.55 produces the lowest error. This would not be significant by the K-S test but the 3.54% maximum error would indicate a fit and calls into question the appropriateness of K-S for large populations of authors.
-
Raan, A.F.J. van: Statistical properties of bibliometric indicators : research group indicator distributions and correlations (2006)
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- Date
- 22. 7.2006 16:20:22
-
Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009)
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- Date
- 22. 3.2009 19:22:35
-
Marshakova-Shaikevich, I.: ¬The standard impact factor as an evaluation tool of science fields and scientific journals (1996)
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- Abstract
- Introduces the standard impact factor for particular fields of science (Ig) and the relative impact factor K for scientific journals. The technique for the calculation of the standard impact factor for a field is an inherent part of a methods which allows a cross field evaluation of scientific journals. This method for evaluating scientific journals elaborated in 1988 was aimed at the analysis of Russian journals covered by the SCI database; it was also used for chemical journals and for journals in the life sciences
-
Li, T.-C.: Reference sources in periodicals : research note (1995)
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- Abstract
- Presents a list of 53 periodicals in 22 subject fields which regularly provide bibliographies of theses, research in progress and patents in their particular subject field. The fields of business, economics, history and literature have most periodical listings of dissertations and theses. Also lists 63 periodicals in 25 sub-disciplines which provide rankings or ratings. Rankings and ratings information predominates in the fields of business, sports and games, finance and banking, and library and information science
-
Pichappan, P.; Sangaranachiyar, S.: Ageing approach to scientific eponyms (1996)
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- Footnote
- Report presented at the 16th National Indian Association of Special Libraries and Information Centres Seminar Special Interest Group Meeting on Informatrics in Bombay, 19-22 Dec 94
-
Mommoh, O.M.: Subject analysis of post-graduate theses in library, archival and information science at Ahmadu Bello University, Zaria (1995/96)
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- Source
- Library focus. 13/14(1995/96), S.22-25
-
Chongde, W.; Zhe, W.: Evaluation of the models for Bradford's law (1998)
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- Date
- 22. 5.1999 19:12:28
-
Tijssen, R.J.W.; Wijk, E. van: ¬The global science base of information and communication technologies : bibliometric analysis of ICT research papers (1998)
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- Date
- 22. 5.1999 19:26:54
-
Rostaing, H.; Barts, N.; Léveillé, V.: Bibliometrics: representation instrument of the multidisciplinary positioning of a scientific area : Implementation for an Advisory Scientific Committee (2007)
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- Date
- 30.12.2007 11:22:39
-
Scholarly metrics under the microscope : from citation analysis to academic auditing (2015)
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- Date
- 22. 1.2017 17:12:50
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Date
- 22. 8.2014 17:05:18
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Ohly, P.: Dimensions of globality : a bibliometric analysis (2016)
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- Date
- 20. 1.2019 11:22:31
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Yoshikane, F.; Kageura, K.; Tsuji, K.: ¬A method for the comparative analysis of concentration of author productivity, giving consideration to the effect of sample size dependency of statistical measures (2003)
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Järvelin, K.; Persson, O.: ¬The DCI index : discounted cumulated impact-based research evaluation (2008)
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- Content
- Erratum in: Järvelin, K., O. Persson: The DCI-index: discounted cumulated impact-based research evaluation. Erratum re. In: Journal of the American Society for Information Science and Technology. 59(2008) no.14, S.2350-2352.
-
Schreiber, M.: Inconsistencies of recently proposed citation impact indicators and how to avoid them (2012)
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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.
-
Buchholz, K.: Criteria for the analysis of scientific quality (1995)
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