Abstract
Most governmental research assessment exercises do not use citation data for the Social Sciences and Humanities as Web of Science or Scopus coverage in these disciplines is considered to be insufficient. We therefore assess to what extent Google Scholar can be used as an alternative source of citation data. In order to provide a credible alternative, Google Scholar needs to be stable over time, display comprehensive coverage, and provide non-biased comparisons across disciplines. This article assesses these conditions through a longitudinal study of 20 Nobel Prize winners in Chemistry, Economics, Medicine and Physics. Our results indicate that Google Scholar displays considerable stability over time. However, coverage for disciplines that have traditionally been poorly represented in Google Scholar (Chemistry and Physics) is increasing rapidly. Google Scholar’s coverage is also comprehensive; all of the 800 most cited publications by our Nobelists can be located in Google Scholar, although in four cases there are some problems with the results. Finally, we argue that Google Scholar might provide a less biased comparison across disciplines than the Web of Science. The use of Google Scholar might therefore redress the traditionally disadvantaged position of the Social Sciences in citation analysis.
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Notes
Humanities are not included in the Essential Science Indicators. We acknowledge that the high ranking for Australia in the Social Sciences/Economics & Business is partly caused by its “English-language” advantage. ISI has a bias towards English-language journals and local language journals are more common in the Social Sciences than in the Sciences and Medicine. However, this does not invalidate the argument as ISI listed journals are generally perceived to be top journals in their fields; many Australian journals are not ISI listed either. Hence Australia still punches above its weight. Moreover, although one can quibble with the number of papers measure, the citations per paper measure shows that the Social Sciences perform on par with the Sciences and Medicine.
As small sample sizes can easily distort the citations per paper metric, we ignored countries that had published less than 100 articles a year.
This was clearly illustrated when we attempted to do a rough assessment of how much a Cited Reference Search would add to our results. For Chemist EJ Corey, more than 2200 of his nearly 3300 entries were to non-ISI listed publications, but 90% of these were stray citations to three journals that are in fact ISI listed. For Physicist Geim, stray citations made up a third of his records for less than 1 % of his citation count.
Economist Paul Krugman for instance had 567 entries in the Science databases, even though all of these publications were books or publications in Economic journals.
We are fully aware that a Cited Reference Search would provide a higher citation count and h-index for Economics. However, it still provides a very incomplete citation record for these Nobelists as it only measures citations in ISI listed journals and it only reports citations to non-ISI listed publication for the first author. For the two Economists where we could reliably search in the Cited Reference search, it provided 8–10 times as many items as the General Search, but as most of these were stray citations, the Cited Reference Search found only 10–20% of the additional Google Scholar citation count. Moreover, our analysis for the Nobelists top-20 journal articles shows that even for ISI-listed publications Google Scholar provides 3–5 times as many citations.
Citations for the other Nobelists in our sample also increased with a similar magnitude (between 0.3 and 1.4 %, with most sitting around 0.6–0.7 %). This seems to suggest that there was no further expansion of coverage in these 4 weeks and that any increase in citations was caused by the natural increase in citations over time. This presents additional evidence of the stability of Google Scholar.
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Harzing, AW. A preliminary test of Google Scholar as a source for citation data: a longitudinal study of Nobel prize winners. Scientometrics 94, 1057–1075 (2013). https://doi.org/10.1007/s11192-012-0777-7
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DOI: https://doi.org/10.1007/s11192-012-0777-7