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    <titleInfo>
        <title>Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section</title>
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    <name type="personal">
        <namePart type="given">Vasudev</namePart>
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            <title>Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion</title>
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        <name type="personal">
            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
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        <name type="personal">
            <namePart type="given">John</namePart>
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            <namePart type="family">McCrae</namePart>
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        <name type="personal">
            <namePart type="given">Manel</namePart>
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        <name type="personal">
            <namePart type="given">Kalika</namePart>
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    <abstract>The proliferation of Hate Speech and misinformation in social media is fast becoming a menace to society. In compliment, the dissemination of hate-diffusing, promising and anti-oppressive messages become a unique alternative. Unfortunately, due to its complex nature as well as the relatively limited manifestation in comparison to hostile and neutral content, the identification of Hope Speech becomes a challenge. This work revolves around the detection of Hope Speech in Youtube comments, for the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion. We achieve an f-score of 0.93, ranking 1st on the leaderboard for English comments.</abstract>
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%0 Conference Proceedings
%T Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section
%A Awatramani, Vasudev
%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 awatramani-2021-hopeful
%X The proliferation of Hate Speech and misinformation in social media is fast becoming a menace to society. In compliment, the dissemination of hate-diffusing, promising and anti-oppressive messages become a unique alternative. Unfortunately, due to its complex nature as well as the relatively limited manifestation in comparison to hostile and neutral content, the identification of Hope Speech becomes a challenge. This work revolves around the detection of Hope Speech in Youtube comments, for the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion. We achieve an f-score of 0.93, ranking 1st on the leaderboard for English comments.
%U https://aclanthology.org/2021.ltedi-1.24
%P 164-167

Markdown (Informal)

[Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section](https://aclanthology.org/2021.ltedi-1.24) (Awatramani, LTEDI 2021)

• Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section (Awatramani, LTEDI 2021)

ACL

• Vasudev Awatramani. 2021. Hopeful NLP@LT-EDI-EACL2021: Finding Hope in YouTube Comment Section. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 164–167, Kyiv. Association for Computational Linguistics.