Methods for estimating the size of Google Scholar

Abstract

The emergence of academic search engines (mainly Google Scholar and Microsoft Academic Search) that aspire to index the entirety of current academic knowledge has revived and increased interest in the size of the academic web. The main objective of this paper is to propose various methods to estimate the current size (number of indexed documents) of Google Scholar (May 2014) and to determine its validity, precision and reliability. To do this, we present, apply and discuss three empirical methods: an external estimate based on empirical studies of Google Scholar coverage, and two internal estimate methods based on direct, empty and absurd queries, respectively. The results, despite providing disparate values, place the estimated size of Google Scholar at around 160-165 million documents. However, all the methods show considerable limitations and uncertainties due to inconsistencies in the Google Scholar search functionalities.

Scholarly social media profiles and libraries

“…However, what the author gains at the setup is easily lost while trying to consolidate data, correct items wrongfully attributed to him or her, and add missing items. This application claims to be a research project created to follow information seeking in academia, and has not been updated (Orduna-Malea, Ayllon, Martin-Martin, & Lopez-Cozar, 2014). GS tends to overinflate researchers' scholarship, while Microsoft Academic Search is just the opposite.…”

Untitled

“…Indeed, to quote (Somerville & Conrad, 2014), "Google Scholar Library, which enables saving articles directly from the search page in Google Scholar, organizing them by topic, and searching full-text documents within a personal MyLibrary space, is setting heightened expectations for workflow integration solutions". Google Scholar does not disclose the list of journals covered, but is independently estimated to index between 100 and 160 million scholarly documents (Khabsa & Giles, 2014;Orduña-Malea, Ayllón, Martín-Martín, & López-Cózar, 2014).…”

“…Figure 4 shows the growth in the number of active, peer-reviewed journals recorded in Ulrich's directory between 2002 and 2012; over this period the number grew by about 2.5% a year. At the time of writing, the CrossRef database included over 71 million DOIs, of which 55 million refer to journal articles from a total of over 36,000 journals.More broadly, Google Scholar is estimated to index between 100 and 160 million documents including journal articles, books, and grey literature (Khabsa & Giles, 2014;Orduña-Malea et al, 2014), while the Web of Science database includes about 90 million records.…”

Un panorama académico de dos caras: retrato de los documentos altamente citados en Google Scholar (1950-2013)

“…Its wide coverage and evolution (Aguillo, 2012;Khabsa & Giles, 2014;Ortega, 2014;Winter et al, 2014;Orduna-Malea et al, 2015) as well as its empirically tested capacity to obtain unique citations (citations that can only be found in Google Scholar) (Yang & Meho, 2006;Meho & Yang, 2007;Kousha & Thelwall, 2008;Bar-Ilan, 2010;Kousha et al, 2011;Harzing, 2014;Orduna-Malea & Delgado López-Cózar, 2014), make of Google Scholar an exceptional source to collect highly-cited documents.…”

“…These errors have been already studied and classified (Jacsó, 2005;2006;Bar-Ilan 2010;Jacsó 2008a;2008b;. Although the quality of the data has improved significantly over the years (Google Scholar is now over 11 years old), some of these errors still persist, especially those related to the detection of duplicate documents, and the correct allocation of citations Orduna-Malea et al, 2015). Thus, Google Scholar data usually requires some cleaning before it is suitable for analysis.…”