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        <title>Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection</title>
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        <namePart type="given">Debora</namePart>
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            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
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    <abstract>In this paper, we describe our approach for the task of homophobia and transphobia detection in English social media comments. The dataset consists of YouTube comments, and it has been released for the shared task on Homophobia/Transphobia Detection in social media comments. Given the high class imbalance, we propose a solution based on data augmentation and ensemble modeling. We fine-tuned different large language models (BERT, RoBERTa, and HateBERT) and used the weighted majority vote on their predictions. Our proposed model obtained 0.48 and 0.94 for macro and weighted F1-score, respectively, ranking at the third position.</abstract>
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%0 Conference Proceedings
%T Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection
%A Nozza, Debora
%Y Chakravarthi, Bharathi Raja
%Y Bharathi, B.
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F nozza-2022-nozza
%X In this paper, we describe our approach for the task of homophobia and transphobia detection in English social media comments. The dataset consists of YouTube comments, and it has been released for the shared task on Homophobia/Transphobia Detection in social media comments. Given the high class imbalance, we propose a solution based on data augmentation and ensemble modeling. We fine-tuned different large language models (BERT, RoBERTa, and HateBERT) and used the weighted majority vote on their predictions. Our proposed model obtained 0.48 and 0.94 for macro and weighted F1-score, respectively, ranking at the third position.
%R 10.18653/v1/2022.ltedi-1.37
%U https://aclanthology.org/2022.ltedi-1.37/
%U https://doi.org/10.18653/v1/2022.ltedi-1.37
%P 258-264

Markdown (Informal)

[Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection](https://aclanthology.org/2022.ltedi-1.37/) (Nozza, LTEDI 2022)

• Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection (Nozza, LTEDI 2022)

ACL

• Debora Nozza. 2022. Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 258–264, Dublin, Ireland. Association for Computational Linguistics.