CNN 新闻政治文章中的构词过程分析

Ni Wayan Swarniti
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引用次数: 0

摘要

词形分析通常包括识别词的各个部分,或者更严格地说,识别词的组成成分。本研究的目的是对美国有线电视新闻网(CNN News)在线新闻平台上发布的政治文章中的构词过程进行分类和分析,尤其是派生词素。研究人员采用了定性研究方法。采用的数据收集技术是观察法。对分析结果进行了详细说明。分析结果显示,有 11 个后缀被归类为形容词派生词,15 个后缀被确定为名词派生词,5 个后缀被归类为动词派生词,具有改变词义功能的词缀有 16 个前缀和 5 个后缀。具有改变词义功能的词缀数量最多。这说明 CNN 新闻更倾向于使用简单有效的词语,使读者易于理解,更有兴趣阅读 CNN 新闻中的其他新闻,尤其是政治类文章。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Analysis of Word Formation Processes in CNN News Political Articles
Morphological analysis typically consists of the identification of parts of words or more technically, constituents of words. The purpose of this research is to classify and analyze the process of word formation, especially derivational morphemes in political articles posted on the CNN News online news platform. The researcher used a qualitative research method. Data collecting technique used was observation. The results of the analysis were explained in detail. Results of the analysis was 11 suffixes found that classified as adjective derivation, 15 suffixes were identified as noun derivation, 5 suffixes was classified as verb derivation, and affixes that have function to change the meaning of word was 16 prefixes and 5 suffixes. The highest number of affixes found was affixes that have function to change the meaning of word. It meant that it prefer to use simple and effective words to make the readers easy to understand and more interested in reading another news in CNN News especially political articles.
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