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A Comparative Study Of The Lexical Patterns Of Emotion-Related Signs In Chinese And American Sign Languages

Posted on:2016-10-11Degree:MasterType:Thesis
Country:ChinaCandidate:L Z ZhangFull Text:PDF
GTID:2285330473959983Subject:English Language and Literature
Abstract/Summary:PDF Full Text Request
Sign language often uses hands to shape tangible things. However, emotions are abstract and invisible concepts, so it is very hard for signers to imitate emotions by means of hand gestures directly. Cognitive linguists find that emotions are mainly conceptualized by metaphors and metonymies. Sign language linguistics introduced this view into the study on sign language and emotions and found that emotion-related words in sign language can be expressed and understood by the two lexical patterns, metaphors and metonymies.This thesis plans to make a comparative study on the two emotional lexical patterns---metaphors and metonymies---of emotional-related signs between CSL and ASL, and meanwhile explore the similarities and differences of the metaphors and metonymies in CSL and ASL. The emotional signs of happiness, anger, sadness and fear in CSL and ASL are the objects of this study. The study shows that the emotion-related signs in both CSL and ASL are largely motivated and expressed by conceptual metaphors and metonymy. Similarities and differences of the metaphors and metonymies between CSL and ASL emotional signs exist. The causes of the similarities are the shared physiological mechanism, cognitive models and the similar psychological experience by all the human beings while cultural variation and different choices of perspectives are the two factors which lead to the differences.Metaphors and metonymies pervade the emotional signs in CSL and ASL. This study provides a support to the cognitive linguistics’view that metaphor is a way of thinking rather than merely a means of rhetoric, and so does the metonymy.
Keywords/Search Tags:conceptual metaphor, conceptual metonymy, basic emotions, sign language, cognition
PDF Full Text Request
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