On Using Corpus Frequency, Dispersion, and Chronological Data to Help Identify Useful Collocations
Author(s) -
James E. Thorold Rogers,
Chris Brizzarda,
Frank E. Daulton,
Cosmin Florescu,
Ian Maclean,
Kayo Mimura,
John O’Donoghue,
Masaya Okamoto,
Gordon Reid,
Yoshiaki Shimada
Publication year - 2015
Publication title -
deleted journal
Language(s) - English
Resource type - Journals
eISSN - 2187-2759
pISSN - 2187-2767
DOI - 10.7820/vli.v04.2.rogers.et.al
Subject(s) - computer science , natural language processing , dispersion (optics) , artificial intelligence , physics , optics
This study analyzed corpus data to determine the extent to which frequency, dispersion, and chronological data can help identify useful collocations for second language learners who aim to master general English. The findings indicated that although various analysis levels of frequency and dispersion data are largely effective, the analyses could not identify useful collocations reliably. The findings also indicated that chronological data analysis is not as useful as dispersion analysis due to the amount of time it took versus the improvements that resulted from it. Ultimately, it was found that a manual analysis of data using native speaker intuition is unavoidable. This study highlighted the value and reliability of certain types of corpus data analysis, and also the necessity of labor-intensive, native speaker analysis for identifying useful collocations.
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