Use of Google Scholar in corpus-driven EAP research

This primarily methodological article makes a proposition for linguistic exploration of textual resources available through the Google Scholar search engine. These resources (Google Scholar virtual corpus) are significantly larger than any existing corpus of academic writing. Google Scholar, however, was not designed for linguistic searches and special attention therefore needs to be paid to maximising its effectiveness in corpus linguistics research. The article discusses the search capacity of Google Scholar and compares the Google Scholar virtual corpus with the largest traditional corpus of written academic English, COCA – academic. Finally, the article offers a case study on the as-author-reporting verb structure (and its modifications). The study demonstrates that Google Scholar can be employed effectively in EAP research offering us new insights into reporting practices in two disciplines, Applied Linguistics and Physics, which were chosen for comparison. The benefits of using Google Scholar virtual corpus are the following: 1) wide representativeness of written academic language, 2) possibility of capturing subtle variation in academic patterns, and 3) possibility of comparing linguistic patterns across different academic fields.

► The use of Google Scholar in corpus-based EAP research is discussed.
► Google Scholar corpus: large, representative and available.
► Google Scholar corpus compared with COCA – academic.
► A case study on “as-author-reporting verb” structure (and its modifications).
► Evidence for different disciplinary conventions in Applied Linguistics and Physics.