Lexico-semantic actualization of the word “success” in the English language: A corpus approach

The research aims to identify the lexico-semantic features of the word “success” in the English language, using data from the Corpus of Contemporary American English (COCA). The research employed lexicographic analysis of the word “success” within large corpora of English texts. Particular attention is paid to corpus linguistic methods, which allowed for the identification of main models of attributive collocations with the studied lexeme. The article examines the most frequent collocations with the noun “success” occurring more than 100 times in the corpus. The analyzed collocations were grouped thematically. The novelty of the research lies in identifying and systematizing the semantic features of the lexeme “success” based on corpus data analysis, which makes it possible to establish current collocation models and determine the specificity of the actualization of the lexeme “success” in contemporary American English. As a result, the research identified three main models of collocation formation with the lexeme “success”. The collocations used most often describe the magnitude of success, the methods and probability of its achievement. Attributes reflecting its interdisciplinarity and defining aspects of positive and negative experience within the context of successful activity are also used.

Authors

Institutions

Publication Details

Journal
Philology Theory & Practice
Published
2024-11-27
DOI
https://doi.org/10.30853/phil20240594
Citations
1
Primary Topic
Language, Communication, and Linguistic Studies
Type
article
Field-Weighted Citation Impact
0.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lexico-semantic actualization of the word “success” in the English language: A corpus approach

Aminet Muratovna Aitekova
1 citations
Philology Theory & Practice
Language, Communication, and Linguistic Studies
0.96
article

Lexico-semantic actualization of the word “success” in the English language: A corpus approach

Aminet Muratovna Aitekova
article en
1 citations

Abstract

The research aims to identify the lexico-semantic features of the word “success” in the English language, using data from the Corpus of Contemporary American English (COCA). The research employed lexicographic analysis of the word “success” within large corpora of English texts. Particular attention is paid to corpus linguistic methods, which allowed for the identification of main models of attributive collocations with the studied lexeme. The article examines the most frequent collocations with the noun “success” occurring more than 100 times in the corpus. The analyzed collocations were grouped thematically. The novelty of the research lies in identifying and systematizing the semantic features of the lexeme “success” based on corpus data analysis, which makes it possible to establish current collocation models and determine the specificity of the actualization of the lexeme “success” in contemporary American English. As a result, the research identified three main models of collocation formation with the lexeme “success”. The collocations used most often describe the magnitude of success, the methods and probability of its achievement. Attributes reflecting its interdisciplinarity and defining aspects of positive and negative experience within the context of successful activity are also used.

Philology Theory & PracticeVol. 17(11)
Adyghe State University (RU)
Quality Education
Openalex Percentile: Top 19%
Language, Communication, and Linguistic Studies
0.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.