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Cited by 375

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

International journal of English studies

Open access
·2021·International Journal of English Studies
DOI 10.6018/ijes
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Abstract

This paper presents a corpus-based analysis of printed eco-friendly car advertisements in English in line with the growing consumer interest in environmental issues and the development of green advertising.The aim of the research is threefold: 1) to unveil the content cognitive operations (for the purpose of this research, metonymy, metonymic chain, metaphoric amalgam and metaphor) underlying the ads and their modes of representation; 2) to examine the relationship between (i) these conceptual operations and the environmental claims made by advertisers, and (ii) the environmental claims made by advertisers and the text-image interaction.In this light, the paper yields two major findings: a) the cognitive operations underlying our corpus are usually rendered in the visual and verbal modes; b) the environmental claims underlying the ads correlate with the conceptual content and the text-image interplay.The conscious use of these mechanisms by advertisers can help the manner in which messages are interpreted.

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Citations

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Cited by

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Metadata

Venue
International Journal of English Studies
Publisher
Servicio de Publicaciones de la Universidad de Murcia
Published
2021-01-08
ISSN
  • 1578-7044 (ISSN-L)
  • 1989-6131
DOI
10.6018/ijes
OpenAlex
W2531452435
Cited by
375
References
25
Type
paratext
Language
en
Open access
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CoChat. (2026). Citation check: International journal of English studies. https://app.cochat.ai/papers/10.6018/ijes
The paper
International journal of English studies. (2021). International Journal of English Studies. https://doi.org/10.6018/ijes

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.