همایش رویکردهای میان رشته ای به آموزش زبان، ادبیات و مطالعات ترجمه

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صفحه اصلی / پنجمین همایش رویکردهای میان رشته ای به آموزش زبان، ادبیات و مطالعات ترجمه

Computer-assisted and AI-assisted Critical Discourse Analysis: Using Digital Technologies to Uncover Power Relations and Inequality in Language

نویسندگان :

Reza Khany¹ Mohammad Mahdi Maadikhah²

1- Ilam University 2- دانشگاه ایلام

کلمات کلیدی :

artificial intelligence in applied linguistics،computers in applied linguistics،critical discourse analysis (CDA)،machine learning (ML)،natural language processing (NLP)

چکیده :

Critical discourse analysis (CDA) is a branch of applied linguistics, and an interdisciplinary field with methodological approaches and analytical frameworks involving investigation and exploration of power relations, societal relations and inequality, aiming to raise awareness and ultimately emancipate individuals and social groups. Computers have been used in applied linguistics since their public availability in late 1970s and the 1980s, assisting researchers in various disciplines, especially corpus linguistics. With recent revolutionary advancements and transformations in artificial intelligence (AI), natural language processing (NLP) and machine learning (ML), most, if not all, academic disciplines have adapted solutions to leverage the power, potentials and advantages of these technologies in their inquiries. Application of computers and related digital technologies in CDA has been underexplored. This paper aims to review and propose some of the possible applications of computerized and AI-powered solutions and tools in CDA. Based on the highlights and trends in relevant literature, some of these applications are identification of discursive structures and patterns, detecting tone, sentiment signs, reference, and contextual connections, tracing intertextuality, discovering generalizations, associations, themes and signals, assisting in discourse parsing, topic modeling, frame analysis and bias detection, helping with multimodal analysis, frequency calculation, recognizing and categorizing textual and metatextual elements, and data visualization. AI- and ML-enabled tools can process and analyze large corpora, providing in-depth analysis of linguistic, metalinguistic, stylistic, syntactic, semantic, semiotic and sociolinguistic characteristics of texts to different extents and levels, aiding researchers in understanding the systematic indicators, implications and parameters related to power, inequality and societal relations.