<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="karan-snajder-2019-preemptive">
    <titleInfo>
        <title>Preemptive Toxic Language Detection in Wikipedia Comments Using Thread-Level Context</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Vanja</namePart>
        <namePart type="given">Mladen</namePart>
        <namePart type="family">Karan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jan</namePart>
        <namePart type="family">Šnajder</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Third Workshop on Abusive Language Online</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Sarah</namePart>
            <namePart type="given">T</namePart>
            <namePart type="family">Roberts</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Joel</namePart>
            <namePart type="family">Tetreault</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">Florence, Italy</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We address the task of automatically detecting toxic content in user generated texts. We fo cus on exploring the potential for preemptive moderation, i.e., predicting whether a particular conversation thread will, in the future, incite a toxic comment. Moreover, we perform preliminary investigation of whether a model that jointly considers all comments in a conversation thread outperforms a model that considers only individual comments. Using an existing dataset of conversations among Wikipedia contributors as a starting point, we compile a new large-scale dataset for this task consisting of labeled comments and comments from their conversation threads.</abstract>
    <identifier type="citekey">karan-snajder-2019-preemptive</identifier>
    <identifier type="doi">10.18653/v1/W19-3514</identifier>
    <location>
        <url>https://aclanthology.org/W19-3514</url>
    </location>
    <part>
        <date>2019-08</date>
        <extent unit="page">
            <start>129</start>
            <end>134</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Preemptive Toxic Language Detection in Wikipedia Comments Using Thread-Level Context
%A Karan, Vanja Mladen
%A Šnajder, Jan
%Y Roberts, Sarah T.
%Y Tetreault, Joel
%Y Prabhakaran, Vinodkumar
%Y Waseem, Zeerak
%S Proceedings of the Third Workshop on Abusive Language Online
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F karan-snajder-2019-preemptive
%X We address the task of automatically detecting toxic content in user generated texts. We fo cus on exploring the potential for preemptive moderation, i.e., predicting whether a particular conversation thread will, in the future, incite a toxic comment. Moreover, we perform preliminary investigation of whether a model that jointly considers all comments in a conversation thread outperforms a model that considers only individual comments. Using an existing dataset of conversations among Wikipedia contributors as a starting point, we compile a new large-scale dataset for this task consisting of labeled comments and comments from their conversation threads.
%R 10.18653/v1/W19-3514
%U https://aclanthology.org/W19-3514
%U https://doi.org/10.18653/v1/W19-3514
%P 129-134

Markdown (Informal)

[Preemptive Toxic Language Detection in Wikipedia Comments Using Thread-Level Context](https://aclanthology.org/W19-3514) (Karan & Šnajder, ALW 2019)

• Preemptive Toxic Language Detection in Wikipedia Comments Using Thread-Level Context (Karan & Šnajder, ALW 2019)

ACL

• Vanja Mladen Karan and Jan Šnajder. 2019. Preemptive Toxic Language Detection in Wikipedia Comments Using Thread-Level Context. In Proceedings of the Third Workshop on Abusive Language Online, pages 129–134, Florence, Italy. Association for Computational Linguistics.