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        <title>IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations</title>
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        <namePart type="given">Jorge</namePart>
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    <name type="personal">
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            <title>Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis</title>
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        <name type="personal">
            <namePart type="given">Alexandra</namePart>
            <namePart type="family">Balahur</namePart>
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            <namePart type="given">Saif</namePart>
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    <abstract>In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2nd place out of 30 teams with a test macro F1 score of 0.710. The system is composed of a single pre-trained ELMo layer for encoding words, a Bidirectional Long-Short Memory Network BiLSTM for enriching word representations with context, a max-pooling operation for creating sentence representations from them, and a Dense Layer for projecting the sentence representations into label space. Our official submission was obtained by ensembling 6 of these models initialized with different random seeds. The code for replicating this paper is available at https://github.com/jabalazs/implicit_emotion.</abstract>
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%0 Conference Proceedings
%T IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
%A Balazs, Jorge
%A Marrese-Taylor, Edison
%A Matsuo, Yutaka
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y Hoste, Veronique
%Y Klinger, Roman
%S Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F balazs-etal-2018-iiidyt
%X In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2nd place out of 30 teams with a test macro F1 score of 0.710. The system is composed of a single pre-trained ELMo layer for encoding words, a Bidirectional Long-Short Memory Network BiLSTM for enriching word representations with context, a max-pooling operation for creating sentence representations from them, and a Dense Layer for projecting the sentence representations into label space. Our official submission was obtained by ensembling 6 of these models initialized with different random seeds. The code for replicating this paper is available at https://github.com/jabalazs/implicit_emotion.
%R 10.18653/v1/W18-6208
%U https://aclanthology.org/W18-6208
%U https://doi.org/10.18653/v1/W18-6208
%P 50-56

Markdown (Informal)

[IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations](https://aclanthology.org/W18-6208) (Balazs et al., WASSA 2018)

• IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations (Balazs et al., WASSA 2018)

ACL

• Jorge Balazs, Edison Marrese-Taylor, and Yutaka Matsuo. 2018. IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 50–56, Brussels, Belgium. Association for Computational Linguistics.