基于语料库的批评话语分析实证研究综述

A Review of Empirical Studies on Corpus-Based Critical Discourse Analysis

摘要: 批评话语分析关注语言在社会语境中的动态建构。但传统的定性分析方法在处理大规模语料时存在主观性强、代表性不足等局限性。随着计算语言学和大数据技术的发展，语料库语言学为批评话语分析提供了一种更加科学、客观且可重复验证的研究方法。本文聚焦基于语料库的批评话语分析，以实证研究为切入点，重点分析了其研究话题、研究理论及研究方法。研究结果表明：(1) 在研究话题上，移民与难民、公共卫生、性别议题、政治术语等多个领域受到广泛关注；(2) 在研究理论上，既延续了经典的研究范式，又融入了跨学科理论，以拓展研究视角；(3) 在研究方法上，采用混合研究方法、对比分析方法及语言处理工具，以提升分析的深度与精确性。最后，本文指出当前研究的局限性，并对未来研究提出展望。

Abstract: Critical Discourse Analysis (CDA) focuses on the dynamic construction of language within social contexts. However, traditional qualitative methods often face limitations such as subjectivity and insufficient representativeness when dealing with large-scale data. With the development of computational linguistics and big data technologies, corpus linguistics offers a more scientific, objective, and replicable approach to CDA. This paper reviews empirical studies on corpus-based CDA, focusing on research topics, theoretical frameworks, and methodological approaches. The findings show that: (1) in terms of research topics, areas such as immigration and refugees, public health, gender issues, and political discourse have received widespread attention; (2) in terms of theoretical foundations, studies not only continue classical paradigms but also integrate interdisciplinary theories to broaden analytical perspectives; (3) in terms of methodology, mixed-method approaches, comparative analysis, and linguistic processing tools are adopted to enhance analytical depth and precision. Finally, the paper identifies current research limitations and provides suggestions for future studies.