Abstract
It has been suggested that metaphor often performs some sort of evaluative function. However, there have been few empirical studies addressing this issue. Moreover, little is known about the extent to which a metaphor needs to be creative in order to perform an evaluative function, or whether there are differences according to the type of evaluation, such as its degree of explicitness and its polarity. In order to investigate these questions, 94 film reviews from the Internet Movie Database (IMDB) were annotated for creative and conventional metaphor, and for positive and negative, inscribed and invoked evaluation. Approximately half of the metaphors in our corpus were found to perform an evaluative function. Creative metaphors were significantly more likely to perform an evaluative function than conventional metaphors. Metaphorical evaluation was found to be significantly more negative than non-metaphorical evaluation. Both creative and conventional metaphors were used more frequently to perform inscribed evaluation than invoked evaluation. However, the tendency towards inscribed evaluation was stronger for conventional metaphors than for creative metaphors. From a theoretical perspective, these findings call into question fundamental assumptions about the role of metaphor in performing evaluation, such as the claim, made in the Systemic Functional Linguistics literature, that metaphor invariably ‘provokes’ attitudinal meanings. We have shown that it can do so, but that it does not always do so. The study also offers methodological contributions, by introducing a new protocol for the annotation of creative metaphors as well as detailed guidelines for coding evaluation at different levels of explicitness.
Original language | English |
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Pages (from-to) | 75-103 |
Number of pages | 29 |
Journal | English Language and Linguistics |
Volume | 26 |
Issue number | 1 |
Early online date | 28 Apr 2021 |
DOIs | |
Publication status | Published - 11 Feb 2022 |
Bibliographical note
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- creative metaphor
- invoked evaluation
- Appraisal framework
- manual corpus annotation