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Keyword analysis is one of the most widely used methods in corpus linguistics. The method is used to generate keywords which provide an indication of concepts in texts or a corpus. Keyword analysis tools commonly produce resulting keywords presented as a list which rather poorly indicates what the corpus is about since it typically requires analysts’ knowledge on conceptual associations between keywords. Therefore, common follow-up methods of keyword analysis are to examine concordances, collocational patterns, and some other patterns of associations between keywords and contexts. This study focuses on the association within a group of keywords by constructing a representation of a keyword list as keyword clusters. The keywords for an analysis were generated from two corpora; the target corpus was collected from research articles in applied linguistics and the comparative corpus was a collection of research in pure and applied sciences. The relationship between the top 30 keywords was identifed using mutual information scores of all possible pairs of the keywords within a span of 20 and these scores were used as input for creating keyword clusters. The representations of the 30 keywords as a list and clusters are presented and discussed.
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