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H-Index and Its Variants: Which Variant Fairly Assess Author's Achievements

H-Index and Its Variants: Which Variant Fairly Assess Author's Achievements
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Author(s): Rosy Jan (University of Kashmir, Srinagar, India) and Riyaz Ahmad (University of Kashmir, Srinagar, India)
Copyright: 2020
Volume: 13
Issue: 1
Pages: 9
Source title: Journal of Information Technology Research (JITR)
Editor(s)-in-Chief: Francisco José García-Peñalvo (University of Salamanca, Spain)
DOI: 10.4018/JITR.2020010105


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H-index is an accepted norm to rank scientists and makes them eligible for various professional benefits. However, taking into consideration the associated flaws of the h-index, a diversified set of parameters have been proposed by the scientific community to rank authors in a better way. Imaginary case studies and datasets are used to find out the practical and actual utility of the proposed indicators. To analyze the individual behaviour of each index, these indices are comprehensively evaluated on an extensive data set. This study emphasizes the scrutiny of the h-index, some of its variants, and extensions to rank authors. There appears to be a correlation between high citation rates for a published researcher and the award of prestigious accolades. Thus, the inclusion of a researcher in the list is based on high citation rates and the authority has claimed a direct connection between the citation rates and prestigious awards. In this context, the work initiated to find out the h-index and its variants for the selected researchers incorporated in the hall of citation laureates from the field of medicine. It is clear from the correlation analysis that there is a difference in the degree of correlation between the h-index and its variants. The A-index is weakly correlated, and M-Quotient is strongly correlated with h-index. Thus, most of the h-index variants are merely mathematically and arithmetically modified and does not add any new information as these are highly correlated and are based on the h-core. Thus, more useful and reasonable approaches could be developed for multidimensional and contextualized evaluations of scientific performance rather than cocooning them with mere numbers.

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