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SCIENTIFIC WORK - 2026
https://doi.org/10.36719/2663-4619/112/49-53
Sevinj Taghiyeva
Azerbaijan State Aqrarian University
https://orcid.org/0000-0002-2288-8579
tagiyevas951@gmail.com
Anna Gruzina
Azerbaijan State Agrarian University
https://orcid.org/0000-0003-2422-9996
anna-v-g2004@yandex.ru
Malaika Khudaverdiyeva
Azerbaijan State Agrarian University
https://orcid.org/0009-0006-2540-3772
melaikexudaverdiyeva082@gmail.com
Tamella Alizadeh
Azerbaijan State Agrarian University
https://orcid.org/0009-0001-3324-033X
alizadetamella@gmail.com
Solmaz Ismayilova
Azerbaijan State Agrarian University
https://orcid.org/0009-0003-3354-4506
huseynovasolmaz45@gmail.com
Lexico-Semantic Groups of Words Characterizing a Person in English
Abstract
The article provides a comparative analysis of lexical and semantic groups of words characterizing a person in the Azerbaijani and English languages. It is noted that a comparative study of such a layer of these languages, which includes vocabulary characterizing a person's temper, helps to identify common and individual features, describe the national image, mentality, ethical and moral norms in the culture of the Azerbaijani and English peoples. These groups of words characterizing a person by a variety of features constitute a fairly large volume in the languages under study and represent a set of a number of semantic associations that are grouped by the similarity of certain semantic features. They are divided into smaller groups and subgroups by the components of semantic features within themselves. Each of these subgroups can be considered as a member of another, larger group. Lexical and semantic groups of words defining various properties, attributes, character traits, appearance, as well as moral and ethical qualities of a person are represented quite widely in the languages under study. The listed lexical-semantic groups and subgroups turned out to be closely interconnected and interdependent.
Keywords: languages, lexical-semantic groups, words characterizing a person, comparative analysis, semantic associations
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