A Python based Regression Approach on Reliable Journal Parameters to Assess Few Scientific Impact Measures
نویسندگان
چکیده
The growing use of bibliometrics among researchers has showcased the emergence of various evaluators of scientific research at the author front as well as journal publishers. Several indices has been put forward since the importance of scientific evaluators has gained prominence. Among any such indices, h-index, g-index etc., has been widely used in literature. The regression analysis presented here focus on the citation parameters such as total docs, citable docs, references per doc etc., reported in SCIMago database to evaluate the dependence of these parameters on various indices such as h-index, a-index, m-index, q2 index, r-index, a-r index and e-index respectively. The regression analysis was performed to delineate the dependence of various citation features on index values. From the analysis, it is understood that in all cases except a-index, an increase in SJR value is suggested which means that SJR contributes positively to enhance index factor of journals.
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