Incorporating cross-linguistic and time-based dimensions to Critical Metaphor Analysis : a specialised hands-on analytical approach

Liu, Yufeng and Li, Dechao and Feng, Jieyun (2024) Incorporating cross-linguistic and time-based dimensions to Critical Metaphor Analysis : a specialised hands-on analytical approach. Critical Discourse Studies. ISSN 1740-5904

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Abstract

Critical Metaphor Analysis (CMA) regards metaphor as a fundamental means of conceptualising the world, through which the ideology embedded in discourse can be unveiled. Drawing upon the methodologies of Critical Discourse Analysis and Corpus Linguistics, CMA comprises four principle stages: initially, contextual analysis for formulating research questions and selecting texts, followed by metaphor identification, interpretation, and explanation. This schematic four-stage CMA has found widespread applications in analyses of sensitive discourses, particularly political discourses. This study builds upon these schematic four stages, putting forward a more specialised, hands-on analytical approach that is well suited for a range of research objectives in translation and bi/multilingual settings where both cross-linguistic and time-based perspectives can be considered. To provide a step-by-step guide of this cross-linguistic and time-based analytical approach, this study presents two case studies of the Chinese newspaper Global Times’ Chinese-English bilingual COVID-19 reports in 2020. Specifically, metaphor translation and a time series analysis of the attitudinal intensity (strengthening, weakening, or keeping the negativity towards the pandemic unchanged) as manifested through the translation of WAR metaphors were explored. The study concludes by suggesting the application of this analytical approach to other types of metaphor correspondence and time-based analyses.

Item Type:
Journal Article
Journal or Publication Title:
Critical Discourse Studies
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3300
Subjects:
?? social sciences(all) ??
ID Code:
223864
Deposited By:
Deposited On:
11 Sep 2024 08:30
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Sep 2024 00:49