Bringing metaphors back to the streets: A corpus-based study for the identification and interpretation of rhetorical figures in street art

Research output: Contribution to journalArticle

Abstract

Research on (verbo-) pictorial metaphors and other rhetorical figures is primarily focused on the genre of advertising, leaving other genres under-investigated. In this study, we focus on street art, a visually perceived cross-cultural medium used to address sociopolitical issues. This genre typically combines two interacting semiotic systems – language and depiction – and is thus a form of polysemiotic communication. Our analysis is based on a corpus of 50 street artworks addressing the financial, sociopolitical, and migrant/refugee crisis in the city of Athens (2015-2017). We present a data-driven procedure for the identification and interpretation of metaphors and other rhetorical figures in street art, informed by cognitive linguistic and semiotic models.
Quantitative analyses show that our model can be reliably applied to street art and can enable us to distinguish metaphors from other rhetorical figures within these images. At the same time, qualitative analyses show that this genre usually requires the integration of conceptual, contextual, socio-cultural, and linguistic knowledge in order to achieve successful interpretation of these images.
We discuss our findings within the theoretical framework of Cognitive Semiotics.

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Authors
Organisations
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  • University of Oxford
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • General Language Studies and Linguistics

Keywords

  • (verbo-) pictorial metaphor, cognitive Semiotics, street art, rhetorical figures, metaphor identification, metaphor interpretation
Original languageEnglish
Number of pages35
JournalVisual Communication
Publication statusE-pub ahead of print - 2019 Oct 19
Publication categoryResearch
Peer-reviewedYes

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Related activities

Stampoulidis, G. (Speaker)
2019 Nov 14

Activity: Talk or presentationPublic lecture/debate/seminar

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