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        <title>Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data</title>
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    <name type="personal">
        <namePart type="given">Keith</namePart>
        <namePart type="family">Cortis</namePart>
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    <name type="personal">
        <namePart type="given">Kanishk</namePart>
        <namePart type="family">Verma</namePart>
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    <name type="personal">
        <namePart type="given">Brian</namePart>
        <namePart type="family">Davis</namePart>
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        <dateIssued>2021-09</dateIssued>
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            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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    <abstract>This paper presents multidimensional Social Opinion Mining on user-generated content gathered from newswires and social networking services in three different languages: English —a high-resourced language, Maltese —a low-resourced language, and Maltese-English —a code-switched language. Multiple fine-tuned neural classification language models which cater for the i) English, Maltese and Maltese-English languages as well as ii) five different social opinion dimensions, namely subjectivity, sentiment polarity, emotion, irony and sarcasm, are presented. Results per classification model for each social opinion dimension are discussed.</abstract>
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        <url>https://aclanthology.org/2021.ranlp-1.36</url>
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%0 Conference Proceedings
%T Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data
%A Cortis, Keith
%A Verma, Kanishk
%A Davis, Brian
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
%D 2021
%8 September
%I INCOMA Ltd.
%C Held Online
%F cortis-etal-2021-fine
%X This paper presents multidimensional Social Opinion Mining on user-generated content gathered from newswires and social networking services in three different languages: English —a high-resourced language, Maltese —a low-resourced language, and Maltese-English —a code-switched language. Multiple fine-tuned neural classification language models which cater for the i) English, Maltese and Maltese-English languages as well as ii) five different social opinion dimensions, namely subjectivity, sentiment polarity, emotion, irony and sarcasm, are presented. Results per classification model for each social opinion dimension are discussed.
%U https://aclanthology.org/2021.ranlp-1.36
%P 309-314

Markdown (Informal)

[Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data](https://aclanthology.org/2021.ranlp-1.36) (Cortis et al., RANLP 2021)

• Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data (Cortis et al., RANLP 2021)

ACL

• Keith Cortis, Kanishk Verma, and Brian Davis. 2021. Fine-tuning Neural Language Models for Multidimensional Opinion Mining of English-Maltese Social Data. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 309–314, Held Online. INCOMA Ltd..