A corpus-based approach to emotion metaphors in Korean
A case study of anger, happiness, and sadness
The major goal of this study is to investigate conceptual emotion metaphors of Korean, particularly those of ANGER, HAPPINESS, and SADNESS, by utilizing a corpus-based analysis. The universality of conceptual metaphors continues to be a controversial topic in cognitive linguistics and thus, more cross-linguistic and language-specific studies are needed to support the theoretical framework of the Conceptual Metaphor Theory (CMT). To this end, the current study identifies and examines Korean metaphorical expressions through a conceptual analysis, supported by both quantitative and qualitative methods, and aims to find out the types of concepts with which ANGER, HAPPINESS, and SADNESS are associated, and thus, to what extent these associations comprise primary (universal) and complex (cultural) metaphors, as suggested by the current view of the CMT. I argue that while it is important to distinguish between universal and cultural metaphors, the hierarchical mapping of variation also describes the characteristics of a language vis-à-vis universality or cultural specificity. Furthermore, I claim that the characteristics of metaphorical expressions should also be determined based on analysis of their occurrences in language use. The data suggest a positive correlation between frequency and productivity. Understanding the frequency and productivity of emotion metaphors through analysis of their occurrence in actual language use will allow better understanding and provide a basis for further investigation of native speakers’ cognitive styles and cognitive tendencies.
Keywords: anger, English, happiness, Korean, metaphor, conceptual metaphor, corpus linguistics, emotion, metonymy, sadness, submetaphor
Published online: 28 June 2013
Cited by 7 other publications
Choi, Eunsoo, Yulia Chentsova-Dutton & W. Gerrod Parrott
Herrero-Zorita, Carlos, Clara Molina & Antonio Moreno-Sandoval
Nguyen, Van Trao
This list is based on CrossRef data as of 17 april 2022. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.