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        <title>EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet</title>
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    <name type="personal">
        <namePart type="given">Gilbert</namePart>
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    <name type="personal">
        <namePart type="given">Hussein</namePart>
        <namePart type="family">Jundi</namePart>
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    <name type="personal">
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    <name type="personal">
        <namePart type="given">Wassim</namePart>
        <namePart type="family">El-Hajj</namePart>
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        <dateIssued>2018-06</dateIssued>
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            <title>Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics</title>
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        <name type="personal">
            <namePart type="given">Malvina</namePart>
            <namePart type="family">Nissim</namePart>
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        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">Berant</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Alessandro</namePart>
            <namePart type="family">Lenci</namePart>
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    <abstract>Nowadays, social media have become a platform where people can easily express their opinions and emotions about any topic such as politics, movies, music, electronic products and many others. On the other hand, politicians, companies, and businesses are interested in analyzing automatically people’s opinions and emotions. In the last decade, a lot of efforts has been put into extracting sentiment polarity from texts. Recently, the focus has expanded to also cover emotion recognition from texts. In this work, we expand an existing emotion lexicon, DepecheMood, by leveraging semantic knowledge from English WordNet (EWN). We create an expanded lexicon, EmoWordNet, consisting of 67K terms aligned with EWN, almost 1.8 times the size of DepecheMood. We also evaluate EmoWordNet in an emotion recognition task using SemEval 2007 news headlines dataset and we achieve an improvement compared to the use of DepecheMood. EmoWordNet is publicly available to speed up research in the field on http://oma-project.com.</abstract>
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    <identifier type="doi">10.18653/v1/S18-2009</identifier>
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        <date>2018-06</date>
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%0 Conference Proceedings
%T EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet
%A Badaro, Gilbert
%A Jundi, Hussein
%A Hajj, Hazem
%A El-Hajj, Wassim
%Y Nissim, Malvina
%Y Berant, Jonathan
%Y Lenci, Alessandro
%S Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F badaro-etal-2018-emowordnet
%X Nowadays, social media have become a platform where people can easily express their opinions and emotions about any topic such as politics, movies, music, electronic products and many others. On the other hand, politicians, companies, and businesses are interested in analyzing automatically people’s opinions and emotions. In the last decade, a lot of efforts has been put into extracting sentiment polarity from texts. Recently, the focus has expanded to also cover emotion recognition from texts. In this work, we expand an existing emotion lexicon, DepecheMood, by leveraging semantic knowledge from English WordNet (EWN). We create an expanded lexicon, EmoWordNet, consisting of 67K terms aligned with EWN, almost 1.8 times the size of DepecheMood. We also evaluate EmoWordNet in an emotion recognition task using SemEval 2007 news headlines dataset and we achieve an improvement compared to the use of DepecheMood. EmoWordNet is publicly available to speed up research in the field on http://oma-project.com.
%R 10.18653/v1/S18-2009
%U https://aclanthology.org/S18-2009
%U https://doi.org/10.18653/v1/S18-2009
%P 86-93

Markdown (Informal)

[EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet](https://aclanthology.org/S18-2009) (Badaro et al., *SEM 2018)

• EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet (Badaro et al., *SEM 2018)

ACL

• Gilbert Badaro, Hussein Jundi, Hazem Hajj, and Wassim El-Hajj. 2018. EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNet. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, pages 86–93, New Orleans, Louisiana. Association for Computational Linguistics.