Semantics in corpus linguistics: the basic colour term red in Modern Greek

This paper argues that electronic corpora provide a rich source of data and a useful tool for semantics.More specifically, collocations, semantic preference and semantic prosody of the basic colour term kkkinos ("red") in Modern Greek are examined, using text corpora, such as Greek electronic dictionaries, SEK (Corpus of Greek texts) and Educational Thesaurus of Greek Texts.The results of the research show that such a corpus-based analysis reveals the semantic and pragmatic aspects of language, the linguistic expression of emotion concepts, through conceptual metaphor and metonymy.Collocations with this term seem to reveal a high degree of semantic opacity in the framework of conceptual metaphor.In addition, kkkinos (red) is mainly related to negative semantic prosody, denoting for instance prohibition (kkini zni = red zone, i.e. the area where entry is prohibited), danger/emergency (kkinos sinaerms = red alert), prostitution/immorality kkino fotki (= red light in a tolerance house) and negative emotions such as anger (kkinos san astaks = as red as a lobster), sorrow (kkini trao = red tragedy) and shame (gine kkinos san pantzri (= He turned as red as beetroot).The originality of the research lies in the emergence of the power of context and contextual factors in linguistic analysis, using naturally occurring instances and precise corpus techniques.Regarding the study limitations, the analysis is based on a specific set of corpora (Greek electronic dictionaries, SEK, and Educational Thesaurus of Greek Texts), which, while valuable, may not represent the full diversity of language use in informal, spoken, or contemporary digital contexts (e.g., social media, forums).

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Publication Details

Journal
RESEARCH RESULT Theoretical and Applied Linguistics
Published
2025-09-30
DOI
https://doi.org/10.18413/2313-8912-2025-11-3-0-6
Primary Topic
Categorization, perception, and language
Type
article
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article

Semantics in corpus linguistics: the basic colour term red in Modern Greek

Dimitra Serakioti
RESEARCH RESULT Theoretical and Applied Linguistics
Categorization, perception, and language
article

Semantics in corpus linguistics: the basic colour term red in Modern Greek

Dimitra Serakioti
article en

Abstract

This paper argues that electronic corpora provide a rich source of data and a useful tool for semantics.More specifically, collocations, semantic preference and semantic prosody of the basic colour term kkkinos ("red") in Modern Greek are examined, using text corpora, such as Greek electronic dictionaries, SEK (Corpus of Greek texts) and Educational Thesaurus of Greek Texts.The results of the research show that such a corpus-based analysis reveals the semantic and pragmatic aspects of language, the linguistic expression of emotion concepts, through conceptual metaphor and metonymy.Collocations with this term seem to reveal a high degree of semantic opacity in the framework of conceptual metaphor.In addition, kkkinos (red) is mainly related to negative semantic prosody, denoting for instance prohibition (kkini zni = red zone, i.e. the area where entry is prohibited), danger/emergency (kkinos sinaerms = red alert), prostitution/immorality kkino fotki (= red light in a tolerance house) and negative emotions such as anger (kkinos san astaks = as red as a lobster), sorrow (kkini trao = red tragedy) and shame (gine kkinos san pantzri (= He turned as red as beetroot).The originality of the research lies in the emergence of the power of context and contextual factors in linguistic analysis, using naturally occurring instances and precise corpus techniques.Regarding the study limitations, the analysis is based on a specific set of corpora (Greek electronic dictionaries, SEK, and Educational Thesaurus of Greek Texts), which, while valuable, may not represent the full diversity of language use in informal, spoken, or contemporary digital contexts (e.g., social media, forums).

RESEARCH RESULT Theoretical and Applied LinguisticsVol. 11(3)
Openalex Percentile: Top 70%
Categorization, perception, and language
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