Achieving stability in corpus-based analysis of word types

Abstract Rank-ordered lists of word types are ubiquitous in corpus linguistics and applied linguistics. Word lists are commonly developed as aids for language teaching and learning, vocabulary testing, and language description. Yet, these lists are often produced and used without evaluation of their stability — or replicability — across corpus samples. Our primary objective in this paper is to describe the cumulative state of knowledge regarding the stability of corpus-based word type lists, focusing on three goals that motivate the creation and use of rank-ordered lists: identifying key lexical items for learning or teaching, assessing vocabulary size or knowledge, and identifying all items in a language domain. We show that word type lists are far less stable than researchers and practitioners often assume, although there is substantial variability in stability depending on the goals and methods behind list creation.