Abstract
ABSTRACTGoogle Scholar (GS) is a database that enables researchers to create their scholarly profiles and keeps track of, among others, their citation counts, and h‐ and i10‐index values. GS is now increasingly being used for research evaluation purposes. Although rich in bibliometric data, GS indexes some duplicate publications and citations, and therefore tends to inflate the citation counts to some extent. Based on a small sample of GS profiles of researchers, this paper aims to study the extent by which duplicates change the citation counts and metrics based thereupon. Findings show that duplicates in GS database somewhat inflates the citation metrics. The scale of the problem as well as the effect of dirty data on performance evaluations based on GS citations data need to be studied further using larger samples.
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