A corpus-based study on snake metaphors in Mandarin Chinese and British English

Wei, Lixia and Wong, Bee Eng (2012) A corpus-based study on snake metaphors in Mandarin Chinese and British English. GEMA: Online Journal of Language Studies, 12 (1). pp. 311-324. ISSN 1675-8021

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Abstract

This study is based on the data obtained from the Modern Chinese Corpus compiled by the Center for Chinese Linguistics of Peking University (CCL Corpus) and the British National Corpus (BNC). Via exploring snake metaphors across the two languages within the framework of Conceptual Metaphor Theory and the GREAT CHAIN METAPHOR, this study aims to identify the existence of both universality and individuality of metaphors cross-linguistically when the snake is mapped onto human beings. It investigates the snake metaphors from three aspects. The findings show that, first, the metaphorical expressions in Mandarin Chinese and British English are both mainly generated from the snake’s characteristic and appearance. Second, in terms of the conceptual metaphor of HUMAN BEINGS ARE ANIMALS, Mandarin Chinese and British English share the same metaphor of HUMAN BEINGS ARE SNAKES. However, when the gender of human beings is taken into consideration, the specific conceptual metaphors generalized for the man and the woman from these two languages are different. This provides evidence to show that cross linguistically, like other kinds of conceptual metaphors, the universality of snake metaphors exists at the generic level and the individuality of these metaphors exists at the basic level. Third, in terms of evaluation, the snake metaphorical expressions have a much more derogative meaning for the man in Chinese but a more derogative meaning for the woman in English.

Item Type:Article
Keywords:snake metaphorical expressions; Mandarin Chinese; British English;Conceptual Metaphor Theory; the GREAT CHAIN METAPHOR.
Journal:GEMA ; Online Journal of Language Studies
ID Code:3277
Deposited By: Mr Azam
Deposited On:11 Jan 2012 06:47
Last Modified:14 Dec 2016 06:34

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