东盟英语新闻的句法复杂性与篇章可读性研究

Yusha Zhang, Nankai Lin, Sheng-yi Jiang
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引用次数: 2

摘要

英语是世界上使用最广泛的语言。随着语言的传播和演变,不同地区的英语文本表达和阅读难度存在差异。由于内容和措辞的不同,一些国家的英语新闻比另一些国家的英语新闻更容易理解。使用一种准确有效的方法来计算文本的难度,不仅有利于新闻作者写出易于理解的文章,也有利于读者选择自己能够理解的文章。本文研究了大多数东盟国家、英国和美国在文本可读性方面的差异。我们比较了英国、美国和东盟八个国家(印度尼西亚、马来西亚、菲律宾、新加坡、文莱、泰国、越南、柬埔寨)英语新闻语篇的可读性和句法复杂性。本文选取了各国的权威新闻媒体作为研究对象。本文采用Flesch- kincaid Grade Level (FKG)、Flesch Reading Ease Index (FRE)、Gunning Fog Index (GF)、Automated Readability Index (AR)、Coleman-Liau Index (CL)和Linsear Write Index (LW)等不同指标衡量新闻文本的可读性,并应用L2SCA对新闻文本的句法复杂度进行分析。根据分析结果,我们使用层次聚类方法将不同国家的英语文本划分为六个不同的层次。此外,我们还阐明了这些国家的可读性差异的原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Syntactic Complexity and Text Readability of ASEAN English News
English is the most widely used language in the world. With the spread and evolution of language, there are differences in the English text expression and reading difficulty in different regions. Due to the difference in the content and wording, English news in some countries is easier to understand than in others. Using an accurate and effective method to calculate the difficulty of text is not only beneficial for news writers to write easy-to-understand articles, but also for readers to choose articles that they can understand. In this paper, we study the differences in the text readability between most ASEAN countries, England and America. We compare the textual readability and syntactic complexity of English news texts among England, America and eight ASEAN countries (Indonesia, Malaysia, Philippines, Singapore, Brunei, Thailand, Vietnam, Cambodia). This paper selected the authoritative news media of each country as the research object. We used different indicators including Flesch-Kincaid Grade Level (FKG), Flesch Reading Ease Index (FRE), Gunning Fog Index (GF), Automated Readability Index (AR), Coleman-Liau Index (CL) and Linsear Write Index (LW) to measure the textual readability, and then applied L2SCA to analyze the syntactic complexity of news text. According to the analysis results, we used the hierarchical clustering method to classify the English texts of different countries into six different levels. Moreover, we elucidated the reasons for such readability differences in these countries.
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