@inproceedings{cho-moon-2021-hate,
title = "How Does the Hate Speech Corpus Concern Sociolinguistic Discussions? A Case Study on {K}orean Online News Comments",
author = "Cho, Won Ik and
Moon, Jihyung",
editor = {H{\"a}m{\"a}l{\"a}inen, Mika and
Alnajjar, Khalid and
Partanen, Niko and
Rueter, Jack},
booktitle = "Proceedings of the Workshop on Natural Language Processing for Digital Humanities",
month = dec,
year = "2021",
address = "NIT Silchar, India",
publisher = "NLP Association of India (NLPAI)",
url = "https://aclanthology.org/2021.nlp4dh-1.3",
pages = "13--22",
abstract = "Social consensus has been established on the severity of online hate speech since it not only causes mental harm to the target, but also gives displeasure to the people who read it. For Korean, the definition and scope of hate speech have been discussed widely in researches, but such considerations were hardly extended to the construction of hate speech corpus. Therefore, we create a Korean online hate speech dataset with concrete annotation guideline to see how real world toxic expressions concern sociolinguistic discussions. This inductive observation reveals that hate speech in online news comments is mainly composed of social bias and toxicity. Furthermore, we check how the final corpus corresponds with the definition and scope of hate speech, and confirm that the overall procedure and outcome is in concurrence with the sociolinguistic discussions.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="cho-moon-2021-hate">
<titleInfo>
<title>How Does the Hate Speech Corpus Concern Sociolinguistic Discussions? A Case Study on Korean Online News Comments</title>
</titleInfo>
<name type="personal">
<namePart type="given">Won</namePart>
<namePart type="given">Ik</namePart>
<namePart type="family">Cho</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jihyung</namePart>
<namePart type="family">Moon</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Workshop on Natural Language Processing for Digital Humanities</title>
</titleInfo>
<name type="personal">
<namePart type="given">Mika</namePart>
<namePart type="family">Hämäläinen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Khalid</namePart>
<namePart type="family">Alnajjar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Niko</namePart>
<namePart type="family">Partanen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jack</namePart>
<namePart type="family">Rueter</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>NLP Association of India (NLPAI)</publisher>
<place>
<placeTerm type="text">NIT Silchar, India</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Social consensus has been established on the severity of online hate speech since it not only causes mental harm to the target, but also gives displeasure to the people who read it. For Korean, the definition and scope of hate speech have been discussed widely in researches, but such considerations were hardly extended to the construction of hate speech corpus. Therefore, we create a Korean online hate speech dataset with concrete annotation guideline to see how real world toxic expressions concern sociolinguistic discussions. This inductive observation reveals that hate speech in online news comments is mainly composed of social bias and toxicity. Furthermore, we check how the final corpus corresponds with the definition and scope of hate speech, and confirm that the overall procedure and outcome is in concurrence with the sociolinguistic discussions.</abstract>
<identifier type="citekey">cho-moon-2021-hate</identifier>
<location>
<url>https://aclanthology.org/2021.nlp4dh-1.3</url>
</location>
<part>
<date>2021-12</date>
<extent unit="page">
<start>13</start>
<end>22</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T How Does the Hate Speech Corpus Concern Sociolinguistic Discussions? A Case Study on Korean Online News Comments
%A Cho, Won Ik
%A Moon, Jihyung
%Y Hämäläinen, Mika
%Y Alnajjar, Khalid
%Y Partanen, Niko
%Y Rueter, Jack
%S Proceedings of the Workshop on Natural Language Processing for Digital Humanities
%D 2021
%8 December
%I NLP Association of India (NLPAI)
%C NIT Silchar, India
%F cho-moon-2021-hate
%X Social consensus has been established on the severity of online hate speech since it not only causes mental harm to the target, but also gives displeasure to the people who read it. For Korean, the definition and scope of hate speech have been discussed widely in researches, but such considerations were hardly extended to the construction of hate speech corpus. Therefore, we create a Korean online hate speech dataset with concrete annotation guideline to see how real world toxic expressions concern sociolinguistic discussions. This inductive observation reveals that hate speech in online news comments is mainly composed of social bias and toxicity. Furthermore, we check how the final corpus corresponds with the definition and scope of hate speech, and confirm that the overall procedure and outcome is in concurrence with the sociolinguistic discussions.
%U https://aclanthology.org/2021.nlp4dh-1.3
%P 13-22
Markdown (Informal)
[How Does the Hate Speech Corpus Concern Sociolinguistic Discussions? A Case Study on Korean Online News Comments](https://aclanthology.org/2021.nlp4dh-1.3) (Cho & Moon, NLP4DH 2021)
ACL