The aim of this paper is to expound the characteristics of vocabulary in news articles and to present how to make vocabulary lists for a newspaper class. The corpus of news article texts is analysed in terms of frequency of occurrence and coverage. The result is as follows; Vocabulary in news article texts includes more than 25,000 types. About 80% of vocabulary in news article texts is low-frequency words which appear less than 10 times in the whole corpus of news article texts. Also, vocabulary in news article texts is different from that of the standard corpus as well as vocabulary in Korean texts in its frequency distribution. Especially news article text corpus and Korean text corpus differ from each other in that the former includes words of politics unlike the latter. Based on frequency analysis of word families and text coverage, vocabulary lists for low-frequency words can be made. Word families with a fundamental word, word families with a more frequent word, word families with a semitechnical low-frequency word and word families with low-frequency words should be introduced in a newspaper class in turn. In addition, technical vocabulary in news article texts such as names, places and organizations, appears relatively frequently so that technical vocabulary lists need to be made. These lists of word families in news article texts help instructors not only to make vocabulary material for a newspaper class but also to make possible a more effective current events class dealing with newspaper articles.
1. 머리말
2. 기존 논의의 정리
3. 신문 텍스트의 어휘 분석
4. 맺음말 : 신문 수업용 어휘 목록의 작성 방향
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