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Automated Metaphor Identification in Russian And its Implications for Metaphor Studies

.
Badryzlova Y.

The paper gives an account of a system for automated identification
of linguistic metaphor in Russian text. The design of the system is based on the
five features: semantic heterogeneity, lexical and morphosyntactic metaphor
association, concreteness-abstractness, and topic vectors. Since each of these
features is motivated by a specific set of assumptions about the linguistic and
the cognitive nature of metaphor, we undertake feature analysis, aiming to
reveal possible linguistic and psycholinguistic cues of metaphoricity. Namely,
we extract tentative lexical, morphosyntactic, and topical predictors of
metaphoricity; we also test the hypotheses of correlation between
metaphoricity, on the one hand, and concreteness as well semantic and topical
heterogeneity, on the other.

Language: English
Full text
Keywords: Feature Engineeringlinguistic metaphor identificationmetaphoricity cues

In book

Advances in Cognitive Research, Artificial Intelligence, and Neuroinformatics
Springer, 2020.
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