Volume 24, Issue 3
  • ISSN 1384-6655
  • E-ISSN: 1569-9811
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This paper discusses a variety of potential shortcomings of most of the most widely-used association measures as used in collocation research and collostructional analyses. To address these shortcomings, I then discuss a research program called , an approach that does away with the usual kinds of information conflation by keeping relevant corpus-linguistic dimensions of information – e.g. frequency, association/contingency, dispersion, entropy, etc. – separate and analyzing them in a multidimensional way; I conclude with pointers towards how these dimensions could, if deemed absolutely necessary, be conflated for the simplest kinds of of rankings as well as strategies for future research.


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  • Article Type: Research Article
Keyword(s): collostructional analysis; tupleization
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