The Number of Scholarly Documents on the Public Web

By Madian Khabsa, C. Lee Giles. PLoS ONE, 2014

340 citations recorded by the source corpus.

The number of scholarly documents available on the web is estimated using capture/recapture methods by studying the coverage of two major academic search engines: Google Scholar and Microsoft Academic Search. Our estimates show that at least 114 million English-language scholarly documents are accessible on the web, of which Google Scholar has nearly 100 million. Of these, we estimate that at least 27 million (24%) are freely available since they do not require a subscription or payment of any kind. In addition, at a finer scale, we also estimate the number of scholarly documents on the web for fifteen fields: Agricultural Science, Arts and Humanities, Biology, Chemistry, Computer Science, Economics and Business, Engineering, Environmental Sciences, Geosciences, Material Science, Mathematics, Medicine, Physics, Social Sciences, and Multidisciplinary, as defined by Microsoft Academic Search. In addition, we show that among these fields the percentage of documents defined as freely available varies significantly, i.e., from 12 to 50%.

Subfields: Information Systems

View Paper: https://www.semanticscholar.org/paper/0f3444bbff98eb2f9182f4be1e328e4a1eae309e

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Citations in the corpus

A review of the literature on citation impact indicators (2015, background): “A similar conclusion is reached by Kulkarni et al. (2009) based on an analysis of publications in general medical journals.”
The Role of Google Scholar in Evidence Reviews and Its Applicability to Grey Literature Searching (2015, background): “8 million [3] and 100 million records [4] are identifiable.”
A Review on Fairness in Machine Learning (2022, background): “However, we note that a study from 2014 [119] estimated that Google Scholar covers more than 87% of English scholarly documents available on the web.”
Examining Citations of Natural Language Processing Literature (2020, background): “A Google Scholar Proﬁle page is a user-created page where authors can include their papers (along with the GS-provided citation information for the papers).”
The State of NLP Literature: A Diachronic Analysis of the ACL Anthology (2019, methodology): “We extracted citation information from Google Scholar profiles of authors who had a Google Scholar Profile page and had published at least three papers in the ACL Anthology.”
NRC Publications Archive Archives des publications du CNRC (neutral): “This work is inspired by a vast amount of past research, including that on Google Scholar (Khabsa and Giles, 2014; Howland, 2010; Ordu˜na-Malea et al., 2014; Mart´ın-Mart´ın et al., 2018), on the analysis of NLP papers (Radev et al., 2016; Anderson et al., 2012; Bird et al., 2008; Schluter, 2018;…”