<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="que-2021-simon-lt">
    <titleInfo>
        <title>Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Qinyu</namePart>
        <namePart type="family">Que</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-04</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">John</namePart>
            <namePart type="given">P</namePart>
            <namePart type="family">McCrae</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Manel</namePart>
            <namePart type="family">Zarrouk</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kalika</namePart>
            <namePart type="family">Bali</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Paul</namePart>
            <namePart type="family">Buitelaar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Kyiv</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In today’s society, the rapid development of communication technology allows us to communicate with people from different parts of the world. In the process of communication, each person treats others differently. Some people are used to using offensive and sarcastic language to express their views. These words cause pain to others and make people feel down. Some people are used to sharing happiness with others and encouraging others. Such people bring joy and hope to others through their words. On social media platforms, these two kinds of language are all over the place. If people want to make the online world a better place, they will have to deal with both. So identifying offensive language and hope language is an essential task. There have been many assignments about offensive language. Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI 2021-EACL 2021 uses another unique perspective – to identify the language of Hope to make contributions to society. The XLM-Roberta model is an excellent multilingual model. Our team used a fine-tuned XLM-Roberta model to accomplish this task.</abstract>
    <identifier type="citekey">que-2021-simon-lt</identifier>
    <location>
        <url>https://aclanthology.org/2021.ltedi-1.26</url>
    </location>
    <part>
        <date>2021-04</date>
        <extent unit="page">
            <start>175</start>
            <end>179</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT
%A Que, Qinyu
%Y Chakravarthi, Bharathi Raja
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv
%F que-2021-simon-lt
%X In today’s society, the rapid development of communication technology allows us to communicate with people from different parts of the world. In the process of communication, each person treats others differently. Some people are used to using offensive and sarcastic language to express their views. These words cause pain to others and make people feel down. Some people are used to sharing happiness with others and encouraging others. Such people bring joy and hope to others through their words. On social media platforms, these two kinds of language are all over the place. If people want to make the online world a better place, they will have to deal with both. So identifying offensive language and hope language is an essential task. There have been many assignments about offensive language. Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI 2021-EACL 2021 uses another unique perspective – to identify the language of Hope to make contributions to society. The XLM-Roberta model is an excellent multilingual model. Our team used a fine-tuned XLM-Roberta model to accomplish this task.
%U https://aclanthology.org/2021.ltedi-1.26
%P 175-179

Markdown (Informal)

[Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT](https://aclanthology.org/2021.ltedi-1.26) (Que, LTEDI 2021)

• Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT (Que, LTEDI 2021)

ACL

• Qinyu Que. 2021. Simon @ LT-EDI-EACL2021: Detecting Hope Speech with BERT. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 175–179, Kyiv. Association for Computational Linguistics.