Date of Award
7-24-2020
Thesis Type
Masters
Document Type
Thesis
Divisions
Faculty of Languages and Linguistics
Department
-
Institution
Universiti Malaya
Abstract
This study looks at the semantic prosody of swear words found in a corpus of English songs by looking at their collocations using a corpus software; AntConc. A total of 545 songs were chosen based on the Billboard year-end chart from 2011 to 2016 with 243,689 number of tokens and 8,139 number of word types. Word lists and concordance lines were generated from the corpus for the data analysis. The analysis on the concordance lines showed that not all swear words with negative-based meaning possessed negative semantic prosody. Despite possessing negative semantic prosody, 10 out of 15 swear words possessed neutral semantic prosody and only one word had a positive semantic prosody. In summary, this study argues that swear words are not entirely negative as perceived, rather it depends on context to be regarded as negative.
Additional Information
Dissertation (M.A) – Faculty of Languages and Linguistics, Universiti Malaya, 2020.
Recommended Citation
Hazri Shahreen, Hashim, "A semantic prosody analysis of swear words in a corpus of English songs" (2020). Student Works (2020-2029). 329.
https://knova.um.edu.my/student_works_2020s/329
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Computational Linguistics Commons, Discourse and Text Linguistics Commons, Semantics and Pragmatics Commons
Comments
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