Most corpus-based investigations capitalise on word list analyses: frequency, keyword, and key-keywords, in profiling the lexical features of a specialised language. Though the three word lists have been used in many corpus-based language studies, comparisons across these three types of word lists in characterising a specialised language has not been made to identify any salient information each word list can reveal about the target language. This paper provides comparisons of Engineering English using three types of word list: frequency, keyword and key-keyword lists. The purpose is to identify the lexical information that can be revealed by the groups of words listed according to each type of word lists. To conduct the analyses, a corpus of Engineering English (E²C) is created. All the word lists from the corpus are extracted using the Wordsmith software. Next, further analyses on the distribution of the vocabulary components, namely function vs. content words, and word categories i.e. GSL, AWL and Others, are conducted on all the three word lists. The findings reveal that different word lists result in different ranges of words, and the analyses of the words reveal the distinct features of the specialised language at different levels. Given such differences, this study provides insights into which word lists are to be considered in a lexical study for language description purposes. Hence, this study further verifies the importance of corpus-based lexical investigations in providing empirical evidences for language description.

Keywords: corpus; lexical features; specialised corpus; language description; word lists analysis

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