The lexical semantics of personality words: On ‘shy’ and ‘outgoing’

IF 1.1 3区 文学 0 LANGUAGE & LINGUISTICS
Alena Kazmaly
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引用次数: 0

Abstract

This study addresses linguistic and cross-disciplinary issues connected with the study of personality trait words, e.g., shy, selfish, outgoing. Although the personality lexicon has long been seen as a primary concern for the field of psychology, it is argued here that the study of personality words belongs primarily within the domain of linguistics and can be performed by methods of lexical semantics and corpus analysis. To demonstrate this, two English personality adjectives representative of the personality dimension Extraversion (namely, shy and outgoing) are analysed using a corpus-assisted Natural Semantic Metalanguage (NSM) approach. The results highlight the status of the English words as folk concepts. The risks of excessive reliance on such folk concepts in personality research are demonstrated by the brief comparison with Russian, and alternative ways forward are outlined.

个性词汇的词汇语义:关于 "害羞 "和 "外向
本研究探讨了与人格特质词(如害羞、自私、外向等)研究相关的语言学和跨学科问题。虽然人格词汇长期以来一直被视为心理学领域的主要关注点,但本文认为人格词汇研究主要属于语言学领域,可以通过词汇语义学和语料库分析方法进行。为了证明这一点,我们使用语料库辅助自然语义金属语言(NSM)方法分析了两个代表性格维度外向性的英语性格形容词(即害羞和外向)。结果凸显了这些英语词汇作为民间概念的地位。通过与俄语的简短比较,说明了在人格研究中过度依赖此类民间概念的风险,并概述了其他的前进方向。
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来源期刊
Lingua
Lingua Multiple-
CiteScore
2.50
自引率
9.10%
发文量
93
审稿时长
24 weeks
期刊介绍: Lingua publishes papers of any length, if justified, as well as review articles surveying developments in the various fields of linguistics, and occasional discussions. A considerable number of pages in each issue are devoted to critical book reviews. Lingua also publishes Lingua Franca articles consisting of provocative exchanges expressing strong opinions on central topics in linguistics; The Decade In articles which are educational articles offering the nonspecialist linguist an overview of a given area of study; and Taking up the Gauntlet special issues composed of a set number of papers examining one set of data and exploring whose theory offers the most insight with a minimal set of assumptions and a maximum of arguments.
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