基于Python的能源新闻英语语料库建设与应用
Construction and Application of an English Corpus of Energy News Based on Python
DOI: 10.12677/ml.2026.145462, PDF,    科研立项经费支持
作者: 邓 淼, 白嘉硕：中国矿业大学(北京)文法学院外语系，北京
关键词: 能源；新闻语料库；Python；话语分析；专门用途英语；Energy； News Corpus； Python； Discourse Analysis； ESP
摘要: 全球能源转型、低碳目标及能源安全相关的公共话语，在近年来的国际新闻媒体上热度不减。本文利用Python技术自主构建能源新闻英语语料库，定量结合定性地分析了能源新闻的词汇分布及其高频词搭配的规律性特点。研究结果初步展现了该语料库具有较好的词汇覆盖率，其高频率短语组合也反映出宏观上聚焦绿色发展与多边合作的话语模式是当前主流新闻报道的典型特征；同时本文探讨了将该领域语料库应用于行业趋势预判、政策解读以及商务英语翻译等领域的可行性与应用前景，以期为电力企业预测分析及人才培训提供案例支持与理论参考。
Abstract: Public discourse on energy transition, low-carbon goals, and energy security has remained prominent in international news media in recent years. Using Python, this study independently built an English corpus of energy news and conducted both quantitative and qualitative analyses of the lexical distribution and high-frequency collocational patterns in the corpus. The results demonstrate the corpus’s solid lexical coverage, indicating that a discourse pattern characterized by green development and multilateral cooperation serves as a typical feature in current mainstream news reporting. In addition, this paper explores the potential applications of the corpus in industry forecasting, policy interpretation, and Business English translation, providing theoretical references and case support for predictive analysis and talent training in power enterprises.
文章引用：邓淼, 白嘉硕. 基于Python的能源新闻英语语料库建设与应用[J]. 现代语言学, 2026, 14(5): 805-812. https://doi.org/10.12677/ml.2026.145462

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