基于词频的化学英语可视化分析和教学应用——以Python编程为例

Visualization analysis and teaching applications of Chemistry English based on word frequency using Python programming

摘要

化学英语是高校化学化工类专业教学的重要组成部分。为快速获得重点专业词汇，采用自编的Python程序进行化学英语词频统计，分析了两篇不同化学领域的全面性综述和两个化学类高影响因子国际期刊近年刊载的论文标题，并对结果加以图形化展示。所获高频词汇，可帮助教师备课及学生快速学习专业重点词汇，以及辅助有针对性的论文投稿。研究展示了计算机编程辅助词频统计在化学英语教学实践与研究方面的应用潜力。

Abstract

Chemistry English is an essential component of the teaching in chemistry and chemical engineering majors at colleges and universities. To quickly acquire key professional vocabulary, a self-developed Python program was used to conduct word frequency analysis in Chemistry English. The analysis was based on comprehensive reviews from two different chemical fields and the titles of papers published in two high-impact international chemical journals in recent years. The results were then graphically displayed. The high-frequency vocabulary obtained can help teachers prepare lessons, assist students learn important professional words as well as aid the in targeted paper submissions. This study demonstrated the potential application of computer programming-assisted word frequency statistics in the teaching practice and research of Chemistry English.

关键词

专业英语词汇 / 高频词 / Python编程 / 数据可视化

professional English vocabulary / high-frequency words / Python programming / data visualization

Author summay

滕英来（1983-），男（汉族），湖南东安人，科研助理，博士；