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    <titleInfo>
        <title>The Impact of Figurative Language on Sentiment Analysis</title>
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    <name type="personal">
        <namePart type="given">Tomáš</namePart>
        <namePart type="family">Hercig</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Ladislav</namePart>
        <namePart type="family">Lenc</namePart>
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        <dateIssued>2017-09</dateIssued>
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            <title>Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017</title>
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        <name type="personal">
            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <originInfo>
            <publisher>INCOMA Ltd.</publisher>
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    <abstract>Figurative language such as irony, sarcasm, and metaphor is considered a significant challenge in sentiment analysis. These figurative devices can sculpt the affect of an utterance and test the limits of sentiment analysis of supposedly literal texts. We explore the effect of figurative language on sentiment analysis. We incorporate the figurative language indicators into the sentiment analysis process and compare the results with and without the additional information about them. We evaluate on the SemEval-2015 Task 11 data and outperform the first team with our convolutional neural network model and additional training data in terms of mean squared error and we follow closely behind the first place in terms of cosine similarity.</abstract>
    <identifier type="citekey">hercig-lenc-2017-impact</identifier>
    <identifier type="doi">10.26615/978-954-452-049-6_041</identifier>
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        <date>2017-09</date>
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            <start>301</start>
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%0 Conference Proceedings
%T The Impact of Figurative Language on Sentiment Analysis
%A Hercig, Tomáš
%A Lenc, Ladislav
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F hercig-lenc-2017-impact
%X Figurative language such as irony, sarcasm, and metaphor is considered a significant challenge in sentiment analysis. These figurative devices can sculpt the affect of an utterance and test the limits of sentiment analysis of supposedly literal texts. We explore the effect of figurative language on sentiment analysis. We incorporate the figurative language indicators into the sentiment analysis process and compare the results with and without the additional information about them. We evaluate on the SemEval-2015 Task 11 data and outperform the first team with our convolutional neural network model and additional training data in terms of mean squared error and we follow closely behind the first place in terms of cosine similarity.
%R 10.26615/978-954-452-049-6_041
%U https://doi.org/10.26615/978-954-452-049-6_041
%P 301-308

Markdown (Informal)

[The Impact of Figurative Language on Sentiment Analysis](https://doi.org/10.26615/978-954-452-049-6_041) (Hercig & Lenc, RANLP 2017)

• The Impact of Figurative Language on Sentiment Analysis (Hercig & Lenc, RANLP 2017)

ACL

• Tomáš Hercig and Ladislav Lenc. 2017. The Impact of Figurative Language on Sentiment Analysis. In Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, pages 301–308, Varna, Bulgaria. INCOMA Ltd..