ERIC Number: EJ1372602
Record Type: Journal
Publication Date: 2023-Feb
Pages: 24
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0142-6001
EISSN: EISSN-1477-450X
Which Words Matter Most? Operationalizing Lexical Prevalence for Rank-Ordered Word Lists
Egbert, Jesse; Burch, Brent
Applied Linguistics, v44 n1 p103-126 Feb 2023
The words in a language or language variety are often rank ordered in lists that are meant to reflect the relative importance of those words to language users and learners of a language. This rank ordering is done on the basis of the relative prevalence of words in a corpus. Lexical prevalence is often operationalized as measures of frequency, dispersion, or adjusted frequency. Yet, to date, there is no consensus on best practices for identifying and ranking prevalent words in a corpus, or for evaluating the degree to which a word's importance is reflected through its prevalence. We begin this paper by introducing and describing a wide range of corpus-based measures for quantifying lexical prevalence. We then carry out two case studies on the Duolingo University Textbook Corpus to evaluate the methods for their ability to identify and appropriately rank words in terms of their importance. We conclude with recommendations for word list creators and researchers and practitioners interested in word importance.
Descriptors: Word Lists, Incidence, Computational Linguistics, Textbooks, Word Frequency, Best Practices, Case Studies, Computer Software, Word Recognition, Second Language Learning, Second Language Instruction, Universities, Vocabulary Development, Computer Assisted Instruction
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A