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

Yufeng Liu (Corresponding Author), Dechao Li, Jieyun Feng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

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.

Original languageEnglish
JournalCritical Discourse Studies
DOIs
Publication statusPublished - 9 Sept 2024

Keywords

  • COVID metaphors
  • Critical Metaphor Analysis
  • cross-linguistic difference
  • Global Times
  • metaphor translation
  • news translation
  • time series analysis
  • time variable

ASJC Scopus subject areas

  • General Social Sciences

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