Metaphors and terms in a corpus on political discourse in Persiana cognitive approach

Laburpena

This is a corpus-based study on Persian political discourse in Iran's parliament and two news agencies with different political affiliations. The corpora contain 14 million words collected from January, 2016 to December, 2017. We have applied cognitive linguistics to this study to explore and categorize difficulties and ambiguities for an English-speaking translator translating metaphors and terms from Persian to English. It is a multidisciplinary study that includes cultural, political, religious, translation, cognitive, and corpus studies. Persian metaphorical patterns have been extracted here based on Musolff's (2004 & 2016) scenario-based model for the first time. Furthermore, the Frame-Based Terminology theory has been applied to an inherently abstract domain: political texts. Investigating such big data would be impossible if it were not for Sketch Engine and its unique features and statistics. Based on data analyzed in this study, we have modified Lakoff and Johnson's (1980) model for conceptual metaphors according to the Persian language characteristics. We have shown what metaphors reveal about the hidden agenda of their users. This study has revealed shared conceptual mappings behind political terms and metaphors and their interdependence. Based on the study of terms and metaphors, we have identified a dynamicity of terms specific to Iran's political system and discourse. We have also predicted which concepts' terminology will be more difficult for the English-speaking translator. This study also highlights the importance of extralinguistic knowledge, especially religious knowledge, in translating Persian political texts.