| Sumario: | Although vector space models of word meaning have been successful in modeling many aspects of human semantic knowledge, little research has explored figurative language, such as metaphor, using word vector representations. This article reviews the small body of research that has applied such representations to computational models of metaphor. After providing a short review of vector space models, a detailed overview of metaphor models that make use of vector space, and the relevant empirical findings are discussed. These models are divided into two categories based on their differing motivations: "psychological" models are motivated by modeling the cognitive processes involved in metaphor comprehension whereas "paraphrase" models seek to find the most efficient and accurate way for a computer to paraphrase metaphorical language. These models have been successful in computing adequate metaphor interpretations and shed light on the cognitive processes involved in comprehending metaphor.
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