Metaphors of emotions: towards a data-driven formalization

Formalization of natural language metaphors is a notorious problem in artificial intelligence and other overlapping domains. It semantic vagueness that makes resistant to formulaic or algorithmic descriptions. Great effort has been invested into modeling computationally but the issue remains methodologically uncertain needs further research. This paper works on practical solution how metaphorical meaning can be represented way suitable for computation. The research agenda this interdisciplinary; it brings together an algebraic heuristic-driven theory developed applied comes from cognitive linguistics. postpones theoretical speculation argument solely solution-focused, which contributes value paper’s attempt bridge science disciplines whose compatibility, though declared, seldomdemonstrated piece research.This with human emotions are linguistically manifested modern English discourse. Emotions by virtue their ineffability as qualia rich conceptualizations serve well. meaningful exposes ranks designated properties FEAR, SADNESS, HAPPINESS, RELAXATION/SERENITY concepts arranges these general-purpose ontologies explicitly specify metaphorically preferred emotion good candidates In prospect, will account some aspects probe repetitive nature schemas license expressions language.