Adjective-noun collocation problems: a corpus based study
Keywords:
corpus, collocation, frequency of occurrenceAbstract
It is undeniable that with the development of computer technology, linguistic corpora have developed very rapidly. Due to the use of real language, providing databases of naturally occurring spoken and written discourse, corpora have been applied to various levels of language study. Concerning the lexicon, collocations have received a lot of attention in corpus-based research, which led to substantive improvement in reliability as to choice of collocations for teaching materials. Adjective-noun collocations are explicitly taught in the Headway Advanced textbook. My teaching experience with such textbook led me to question whether the criterion used for presenting them had been either the frequency of occurrence in real language or the authors' intuition. This paper describes a corpus-based study, using the full version of 'Collins CobuildDirect' from the University of Birmingham, in which the frequency of occurrence of the adjective-noun collocations presented in the course book mentioned are investigated. The findings reveal that intuition, rather than empirical evidence, was the criterion used. Assuming that frequency should be given priority in learning and teaching because they are generally required, adjective-noun collocations, which have a more significant frequency of occurrence on the basis of the Cobuild Directdatabase, are suggested.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Revista Horizontes de Linguistica Aplicada

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Articles published by the Journal Horizontes de Linguística Aplicada are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
By publishing in Horizontes de Linguística Aplicada, authors agree to the transfer of economic copyright to the journal. Authors retain their moral rights, including the right to be recognized as the creators of the work.
Authors and readers are free to:
Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes .
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
