A Systematic Literature Review of the Most Frequent Swear Words used by English Language Learners

Swear words also known as profanity, often seen as inappropriate language that play roles in interactions by conveying intense feelings strengthening social connections and making speech more impactful. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, the review synthesizes findings from 25 research articles published between 2009 and 2024 where it examines the most frequent swear words used among English language learners, focusing on the various forms, functions, and contexts in which these words are employed. The studies, drawn from databases such as Scopus, ERIC, and Web of Science (WoS), explore the usage of swear words in different cultural and social contexts, with a particular emphasis on English language learners. The common profane words found are "fuck," "shit," "damn," and "suck," often used in situations such as classrooms, online interactions, social gatherings and media platforms. This analysis showcases the ways in which language learners incorporate these words into their vocabulary. It offers insights for teachers and researchers to comprehend the role of profanity in language acquisition and social interactions. Additionally, the analysis discusses the constraints of research and offers suggestions for further exploration by researchers in this area.

Authors

Publication Details

Journal
International Journal of Academic Research in Progressive Education and Development
Published
2024-09-14
DOI
https://doi.org/10.6007/ijarped/v13-i3/22896
Primary Topic
Swearing, Euphemism, Multilingualism
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Systematic Literature Review of the Most Frequent Swear Words used by English Language Learners

Siti Nur Farahin Faizal, Yasmin Khairani Zakaria
International Journal of Academic Research in Progressive Education and Development
Swearing, Euphemism, Multilingualism
article

A Systematic Literature Review of the Most Frequent Swear Words used by English Language Learners

Siti Nur Farahin Faizal, Yasmin Khairani Zakaria
article en

Abstract

Swear words also known as profanity, often seen as inappropriate language that play roles in interactions by conveying intense feelings strengthening social connections and making speech more impactful. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, the review synthesizes findings from 25 research articles published between 2009 and 2024 where it examines the most frequent swear words used among English language learners, focusing on the various forms, functions, and contexts in which these words are employed. The studies, drawn from databases such as Scopus, ERIC, and Web of Science (WoS), explore the usage of swear words in different cultural and social contexts, with a particular emphasis on English language learners. The common profane words found are "fuck," "shit," "damn," and "suck," often used in situations such as classrooms, online interactions, social gatherings and media platforms. This analysis showcases the ways in which language learners incorporate these words into their vocabulary. It offers insights for teachers and researchers to comprehend the role of profanity in language acquisition and social interactions. Additionally, the analysis discusses the constraints of research and offers suggestions for further exploration by researchers in this area.

International Journal of Academic Research in Progressive Education and DevelopmentVol. 13(3)
Quality Education
Openalex Percentile: Top 79%
Swearing, Euphemism, Multilingualism
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.