@inproceedings{zurbuchen-voigt-2024-computational,
title = "A Computational Analysis and Exploration of Linguistic Borrowings in {F}rench Rap Lyrics",
author = "Zurbuchen, Lucas and
Voigt, Rob",
editor = "Fu, Xiyan and
Fleisig, Eve",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-srw.27",
pages = "294--302",
abstract = "In France, linguistic borrowings in the relatively conservative French language are an important site of cultural debate, and rap in particular is a hotspot for borrowings. In this work, we use computational methods to understand the factors that affect the prominence and prevalence of a borrowing. To do so, we manually annotate a lexicon of over 700 borrowings occurring in this context (including key aspects for each borrowing such as origin and semantic class). We analyze the prevalence of these borrowings in a newly collected corpus of over 8000 French rap song lyrics and find that there are increases in the proportion of linguistic borrowings, interjections, and Niger-Congo borrowings while terms related to the arts are decreasing in prevalence. We release our code and data to facilitate further research in this area and discuss potential future directions.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="zurbuchen-voigt-2024-computational">
<titleInfo>
<title>A Computational Analysis and Exploration of Linguistic Borrowings in French Rap Lyrics</title>
</titleInfo>
<name type="personal">
<namePart type="given">Lucas</namePart>
<namePart type="family">Zurbuchen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rob</namePart>
<namePart type="family">Voigt</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Xiyan</namePart>
<namePart type="family">Fu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Eve</namePart>
<namePart type="family">Fleisig</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Bangkok, Thailand</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>In France, linguistic borrowings in the relatively conservative French language are an important site of cultural debate, and rap in particular is a hotspot for borrowings. In this work, we use computational methods to understand the factors that affect the prominence and prevalence of a borrowing. To do so, we manually annotate a lexicon of over 700 borrowings occurring in this context (including key aspects for each borrowing such as origin and semantic class). We analyze the prevalence of these borrowings in a newly collected corpus of over 8000 French rap song lyrics and find that there are increases in the proportion of linguistic borrowings, interjections, and Niger-Congo borrowings while terms related to the arts are decreasing in prevalence. We release our code and data to facilitate further research in this area and discuss potential future directions.</abstract>
<identifier type="citekey">zurbuchen-voigt-2024-computational</identifier>
<location>
<url>https://aclanthology.org/2024.acl-srw.27</url>
</location>
<part>
<date>2024-08</date>
<extent unit="page">
<start>294</start>
<end>302</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T A Computational Analysis and Exploration of Linguistic Borrowings in French Rap Lyrics
%A Zurbuchen, Lucas
%A Voigt, Rob
%Y Fu, Xiyan
%Y Fleisig, Eve
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F zurbuchen-voigt-2024-computational
%X In France, linguistic borrowings in the relatively conservative French language are an important site of cultural debate, and rap in particular is a hotspot for borrowings. In this work, we use computational methods to understand the factors that affect the prominence and prevalence of a borrowing. To do so, we manually annotate a lexicon of over 700 borrowings occurring in this context (including key aspects for each borrowing such as origin and semantic class). We analyze the prevalence of these borrowings in a newly collected corpus of over 8000 French rap song lyrics and find that there are increases in the proportion of linguistic borrowings, interjections, and Niger-Congo borrowings while terms related to the arts are decreasing in prevalence. We release our code and data to facilitate further research in this area and discuss potential future directions.
%U https://aclanthology.org/2024.acl-srw.27
%P 294-302
Markdown (Informal)
[A Computational Analysis and Exploration of Linguistic Borrowings in French Rap Lyrics](https://aclanthology.org/2024.acl-srw.27) (Zurbuchen & Voigt, ACL 2024)
ACL