Methodological considerations in conducting bibliometric/scientometric reviews

Abstract

Bibliometric and scientometric reviews have become vital in Applied Linguistics, leveraging accessible data from repositories like Scopus and Web of Science to systematically map research outputs. These reviews quantitatively analyse scholarly publications to uncover research topic evolution, key authors, influential articles, citation patterns, and collaboration networks. Scientometric analysis extends this by exploring connections between science and societal, technological, and economic factors. With the surge in scholarly outputs in Applied Linguistics over the past two decades, robust methodological considerations are essential for reliable and transparent bibliometric reviews. This chapter examines these considerations, drawing on two representative studies by the authors focusing on corpus linguistics and written corrective feedback. It discusses critical decisions covering expected (i.e. planned for) and unexpected (i.e. resulting from the data collection and analysis) issues including keyword selection for data retrieval, inclusion/exclusion criteria, challenges with bibliometric data, software and statistical choices, and ensuring diversity and equity in reporting. By synthesising insights from these studies and others, this chapter offers a comprehensive guide for researchers, particularly novices, for conducting bibliometric reviews in Applied Linguistics.