Affiliation:
1. Department of Computer Engineering , Diponegoro University , Tembalang , Semarang , Indonesia
2. Department of Electrical Engineering , Universitas Indonesia , Depok 16424 , Indonesia
Abstract
Abstract
Purpose
This paper proposes a discrimination index method based on the Jain's fairness index to distinguish researchers with the same H-index.
Design/methodology/approach
A validity test is used to measure the correlation of D-offset with the parameters, i.e. H-index, the number of cited papers, the total number of citations, the number of indexed papers, and the number of uncited papers. The correlation test is based on the Saphiro-Wilk method and Pearson's product-moment correlation.
Findings
The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset (D-offset), with a range of D-offset from 0.00 to 0.99. The result of the correlation value between the D-offset and the number of uncited papers is 0.35, D-offset with the number of indexed papers is 0.24, and the number of cited papers is 0.27. The test provides the result that it is very unlikely that there exists no relationship between the parameters.
Practical implications
For this reason, D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index. The H-index for researchers can be written with the format of “H-index: D-offset”.
Originality/value
D-offset is worthy to be considered as a complement value to add the H-index value. If the D-offset is added in the H-index value, the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.
Reference24 articles.
1. Abramo, G., & D’angelo, C.A. (2014). How do you define and measure research productivity? Scientometrics, 101(2), 1129–1144. https://doi.org/10.1007/s11192-014-1269-8
2. Aguillo, I.F. (2018). 2258 Highly Cited Researchers (h>100) according to their Google Scholar Citations public profiles. Retrieved from http://www.webometrics.info/en/node/58
3. Bornmann, L., Mutz, R., Hug, S.E., & Daniel, H.D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5(3), 346–359. https://doi.org/10.1016/j.joi.2011.01.006
4. Daraio, C. (2019). Econometric approaches to the measurement of research productivity. (M. Glänzel, Wolfgang and Moed, Henk F. and Schmoch, Ulrich, and Thelwall, Ed.). Springer International Publishing. https://doi.org/10.1007/978-3-030-02511-3_24
5. Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152. https://doi.org/10.1007/s11192-006-0144-7
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献