<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="niraula-etal-2021-offensive">
    <titleInfo>
        <title>Offensive Language Detection in Nepali Social Media</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nobal</namePart>
        <namePart type="given">B</namePart>
        <namePart type="family">Niraula</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Saurab</namePart>
        <namePart type="family">Dulal</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Diwa</namePart>
        <namePart type="family">Koirala</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Aida</namePart>
            <namePart type="family">Mostafazadeh Davani</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Douwe</namePart>
            <namePart type="family">Kiela</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mathias</namePart>
            <namePart type="family">Lambert</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bertie</namePart>
            <namePart type="family">Vidgen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Vinodkumar</namePart>
            <namePart type="family">Prabhakaran</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Zeerak</namePart>
            <namePart type="family">Waseem</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Social media texts such as blog posts, comments, and tweets often contain offensive languages including racial hate speech comments, personal attacks, and sexual harassment. Detecting inappropriate use of language is, therefore, of utmost importance for the safety of the users as well as for suppressing hateful conduct and aggression. Existing approaches to this problem are mostly available for resource-rich languages such as English and German. In this paper, we characterize the offensive language in Nepali, a low-resource language, highlighting the challenges that need to be addressed for processing Nepali social media text. We also present experiments for detecting offensive language using supervised machine learning. Besides contributing the first baseline approaches of detecting offensive language in Nepali, we also release human annotated data sets to encourage future research on this crucial topic.</abstract>
    <identifier type="citekey">niraula-etal-2021-offensive</identifier>
    <identifier type="doi">10.18653/v1/2021.woah-1.7</identifier>
    <location>
        <url>https://aclanthology.org/2021.woah-1.7</url>
    </location>
    <part>
        <date>2021-08</date>
        <extent unit="page">
            <start>67</start>
            <end>75</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Offensive Language Detection in Nepali Social Media
%A Niraula, Nobal B.
%A Dulal, Saurab
%A Koirala, Diwa
%Y Mostafazadeh Davani, Aida
%Y Kiela, Douwe
%Y Lambert, Mathias
%Y Vidgen, Bertie
%Y Prabhakaran, Vinodkumar
%Y Waseem, Zeerak
%S Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F niraula-etal-2021-offensive
%X Social media texts such as blog posts, comments, and tweets often contain offensive languages including racial hate speech comments, personal attacks, and sexual harassment. Detecting inappropriate use of language is, therefore, of utmost importance for the safety of the users as well as for suppressing hateful conduct and aggression. Existing approaches to this problem are mostly available for resource-rich languages such as English and German. In this paper, we characterize the offensive language in Nepali, a low-resource language, highlighting the challenges that need to be addressed for processing Nepali social media text. We also present experiments for detecting offensive language using supervised machine learning. Besides contributing the first baseline approaches of detecting offensive language in Nepali, we also release human annotated data sets to encourage future research on this crucial topic.
%R 10.18653/v1/2021.woah-1.7
%U https://aclanthology.org/2021.woah-1.7
%U https://doi.org/10.18653/v1/2021.woah-1.7
%P 67-75

Markdown (Informal)

[Offensive Language Detection in Nepali Social Media](https://aclanthology.org/2021.woah-1.7) (Niraula et al., WOAH 2021)

• Offensive Language Detection in Nepali Social Media (Niraula et al., WOAH 2021)

ACL

• Nobal B. Niraula, Saurab Dulal, and Diwa Koirala. 2021. Offensive Language Detection in Nepali Social Media. In Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021), pages 67–75, Online. Association for Computational Linguistics.