<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="rizzi-etal-2024-perspectives">
    <titleInfo>
        <title>Perspectives on Hate: General vs. Domain-Specific Models</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Giulia</namePart>
        <namePart type="family">Rizzi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Michele</namePart>
        <namePart type="family">Fontana</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Elisabetta</namePart>
        <namePart type="family">Fersini</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Gavin</namePart>
            <namePart type="family">Abercrombie</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Valerio</namePart>
            <namePart type="family">Basile</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Davide</namePart>
            <namePart type="family">Bernadi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Shiran</namePart>
            <namePart type="family">Dudy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Simona</namePart>
            <namePart type="family">Frenda</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lucy</namePart>
            <namePart type="family">Havens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sara</namePart>
            <namePart type="family">Tonelli</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>ELRA and ICCL</publisher>
            <place>
                <placeTerm type="text">Torino, Italia</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The rise of online hostility, combined with broad social media use, leads to the necessity of the comprehension of its human impact. However, the process of hate identification is challenging because, on the one hand, the line between healthy disagreement and poisonous speech is not well defined, and, on the other hand, multiple socio-cultural factors or prior beliefs shape people’s perceptions of potentially harmful text. To address disagreements in hate speech identification, Natural Language Processing (NLP) models must capture several perspectives. This paper introduces a strategy based on the Contrastive Learning paradigm for detecting disagreements in hate speech using pre-trained language models. Two approaches are proposed: the General Model, a comprehensive framework, and the Domain-Specific Model, which focuses on more specific hate-related tasks. The source code is available at ://anonymous.4open.science/r/Disagreement-530C.</abstract>
    <identifier type="citekey">rizzi-etal-2024-perspectives</identifier>
    <location>
        <url>https://aclanthology.org/2024.nlperspectives-1.8</url>
    </location>
    <part>
        <date>2024-05</date>
        <extent unit="page">
            <start>78</start>
            <end>83</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Perspectives on Hate: General vs. Domain-Specific Models
%A Rizzi, Giulia
%A Fontana, Michele
%A Fersini, Elisabetta
%Y Abercrombie, Gavin
%Y Basile, Valerio
%Y Bernadi, Davide
%Y Dudy, Shiran
%Y Frenda, Simona
%Y Havens, Lucy
%Y Tonelli, Sara
%S Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F rizzi-etal-2024-perspectives
%X The rise of online hostility, combined with broad social media use, leads to the necessity of the comprehension of its human impact. However, the process of hate identification is challenging because, on the one hand, the line between healthy disagreement and poisonous speech is not well defined, and, on the other hand, multiple socio-cultural factors or prior beliefs shape people’s perceptions of potentially harmful text. To address disagreements in hate speech identification, Natural Language Processing (NLP) models must capture several perspectives. This paper introduces a strategy based on the Contrastive Learning paradigm for detecting disagreements in hate speech using pre-trained language models. Two approaches are proposed: the General Model, a comprehensive framework, and the Domain-Specific Model, which focuses on more specific hate-related tasks. The source code is available at ://anonymous.4open.science/r/Disagreement-530C.
%U https://aclanthology.org/2024.nlperspectives-1.8
%P 78-83

Markdown (Informal)

[Perspectives on Hate: General vs. Domain-Specific Models](https://aclanthology.org/2024.nlperspectives-1.8) (Rizzi et al., NLPerspectives-WS 2024)

• Perspectives on Hate: General vs. Domain-Specific Models (Rizzi et al., NLPerspectives-WS 2024)

ACL

• Giulia Rizzi, Michele Fontana, and Elisabetta Fersini. 2024. Perspectives on Hate: General vs. Domain-Specific Models. In Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024, pages 78–83, Torino, Italia. ELRA and ICCL.