Unveiling semantic complexity of the lexeme ‘reputation’: Corpus analysis
Journal: Russian Journal of Linguistics (Vol.27, No. 3)Publication Date: 2023-10-02
Authors : Svetlana Ivanova; Svetlana Medvedeva;
Page : 615-640
Keywords : collostruction; construction; corpus linguistics; lexeme ‘REPUTATION’; semantic clusterisation; metaphorical collocation;
Abstract
Primarily considered as a form of socially transmitted self-representation, reputation is one of the key concepts in public communication which makes it a worthwhile object for linguistic analysis. The present research is aimed at unveiling the semantic complexity of the lexeme ‘reputation’ by examining its immediate environment in COCA. The study showcases how the closest lexical context enhances the meaning of the lexeme. The sampling under analysis consists of 98 most frequent collocations with adjectives (4,088 tokens) and 57 collocations with verbs (6,190 tokens). The methods of the study include contextual analysis, semantic clusterisation and collostructional analysis based on statistical measure of log-likelihood. As a result, 7 semantic clusters of ‘adjective reputation’ and 8 clusters of ‘verb reputation’ have been obtained. The research proves that discoursewise, the collocations with the lexeme ‘reputation’ are found in newspaper, magazine, blog and web-general sections of COCA. The analysis reveals that in English, reputation is metaphorically represented as a building, a piece of fabric and as a valuable object made of precious metal, where it inherits the properties of tangible objects. A good reputation is earned over time by hard work and, once established, requires monitoring and maintenance. If damaged, it is not thrown away but is to be restored. Metonymically, reputation adopts the qualities of its proprietor (‘notorious reputation’, ‘unfortunate reputation’). The paper contributes to the theory of metaphor and could be beneficial for those working within cultural linguistics, lexicography and translation studies. The research may be further extended with corpus-based analysis of semantically close lexemes.
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Last modified: 2023-10-02 07:22:39