Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: a multidisciplinary comparison

TL;DR

This study compares Google Scholar, Web of Science, and Scopus in covering highly-cited documents across disciplines, revealing significant coverage gaps in Web of Science and Scopus, especially in social sciences and humanities.

Contribution

It provides a multidisciplinary comparison showing that inclusive databases like Google Scholar better identify highly-cited documents than selective databases.

Findings

Google Scholar covers more highly-cited documents in social sciences and humanities.

Citation counts are highly correlated across databases (.83-.99).

Web of Science and Scopus miss a significant portion of highly-cited documents in some fields.

Abstract

This study explores the extent to which bibliometric indicators based on counts of highly-cited documents could be affected by the choice of data source. The initial hypothesis is that databases that rely on journal selection criteria for their document coverage may not necessarily provide an accurate representation of highly-cited documents across all subject areas, while inclusive databases, which give each document the chance to stand on its own merits, might be better suited to identify highly-cited documents. To test this hypothesis, an analysis of 2,515 highly-cited documents published in 2006 that Google Scholar displays in its Classic Papers product is carried out at the level of broad subject categories, checking whether these documents are also covered in Web of Science and Scopus, and whether the citation counts offered by the different sources are similar. The results show that a large fraction of highly-cited documents in the Social Sciences and Humanities (8.6%-28.2%) are invisible to Web of Science and Scopus. In the Natural, Life, and Health Sciences the proportion of missing highly-cited documents in Web of Science and Scopus is much lower. Furthermore, in all areas, Spearman correlation coefficients of citation counts in Google Scholar, as compared to Web of Science and Scopus citation counts, are remarkably strong (.83-.99). The main conclusion is that the data about highly-cited documents available in the inclusive database Google Scholar does indeed reveal significant coverage deficiencies in Web of Science and Scopus in several areas of research. Therefore, using these selective databases to compute bibliometric indicators based on counts of highly-cited documents might produce biased assessments in poorly covered areas.