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The plausibility of computing the h‐index of scholarly productivity and impact using reference‐enhanced databases

The plausibility of computing the h‐index of scholarly productivity and impact using... Purpose – This paper aims to provide a general overview, to be followed by a series of papers focusing on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus, and Web of Science) for determining the h‐index. Design/methodology/approach – The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus and Web of Science). Findings – The h‐index, developed by Jorge E. Hirsch to quantify the scientific output of researchers, has immediately received well‐deserved attention in academia. The theoretical part of his idea was widely embraced, and even enhanced, by several researchers. Many of them also recommended derivative metrics based on Hirsch's idea to compensate for potential distortion factors, such as high self‐citation rates. The practical aspects of determining the h‐index also need scrutiny, because some content and software characteristics of reference‐enhanced databases can strongly influence the h‐index values. Originality/value – The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Online Information Review Emerald Publishing

The plausibility of computing the h‐index of scholarly productivity and impact using reference‐enhanced databases

Péter Jacsó
Online Information Review , Volume 32 (2): 18 – Apr 11, 2008
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References (36)

Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
1468-4527
DOI
10.1108/14684520810879872
Publisher site
See Article on Publisher Site

Abstract

Purpose – This paper aims to provide a general overview, to be followed by a series of papers focusing on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus, and Web of Science) for determining the h‐index. Design/methodology/approach – The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus and Web of Science). Findings – The h‐index, developed by Jorge E. Hirsch to quantify the scientific output of researchers, has immediately received well‐deserved attention in academia. The theoretical part of his idea was widely embraced, and even enhanced, by several researchers. Many of them also recommended derivative metrics based on Hirsch's idea to compensate for potential distortion factors, such as high self‐citation rates. The practical aspects of determining the h‐index also need scrutiny, because some content and software characteristics of reference‐enhanced databases can strongly influence the h‐index values. Originality/value – The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases.

Journal

Online Information Review – Emerald Publishing

Published: Apr 11, 2008

Keywords: Databases; Indexing

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