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Metaphor, Polysemy and Semantic Extension in an Artificial Language Learning Experiment

Creative Commons 'BY' version 4.0 license
Abstract

Polysemy is pervasive in language use and plays a crucial role in enabling the boundless expressive capacity of human language. Semantic extension based on metaphorical associations has been argued to be a key process in words acquiring novel, additional meanings (Anderson, 2017). In this poster, we report the results of an artificial language learning study in which participants had to extend the meaning of previously learned items to refer to new referents. We hypothesised that participants would choose semantic extensions based on metaphoric associations proposed by Conceptual Metaphor Theory (CMT) (Lakoff & Johnson, 1980; Kövecses, 2010). The results indicate that participants seem to make systematic use of salient semantic and metaphoric associations and mappings when having to extend the meanings of learned form-meaning pairings from concrete items to more complex and abstract referents. However only in some cases did participants perform semantic extensions according to our prediction based on CMT.