| Summary: | This research is a corpus-based study with both quantitative and qualitative approaches with the aim of ascertaining the lexical features of business news so as to assist Taiwan's university students in reading business news articles for better comprehension. For this study, a 1.23 million-word corpus was created by collecting business news articles from English language newspapers published in Taiwan. This corpus was used to investigate the word frequency of business news genre. Based on the word frequency, other lexical features were also investigated. These features include word type distribution, coverage of the General Service Word List (GSL) and the Academic Word List (AWL) in the corpus, the applications of Zipf's Law and Powers' vocabulary prediction theory on the business news genre, and an analysis of the lexical difficulty of articles written by local journalists based in Taiwan and by press agency journalists. The suitability of the vocabulary in Business English textbooks commonly used in Taiwan's universities was also assessed in this study. In light of there being no business news word lists available, two word lists - one general with 2,200 words, the other business-specific with 700 words - were compiled, based on the corpus created for this study. The first word list aims to help students gain a lexical knowledge which can cover 95% of business news text; the second one, narrowed down from the first word list, is a condensed, quick- view word list of business terminology. These two word lists, derived from a business news genre, were created for EFLlESL students to prioritise, and aims to help students make efficient and effective progress in their comprehension of business news.
|
|---|
