@inproceedings{plaza-del-arco-etal-2018-sinai-iest,
title = "{SINAI} at {IEST} 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification",
author = "Plaza-del-Arco, Flor Miriam and
Mart{\'\i}nez-C{\'a}mara, Eugenio and
Martin, Maite and
Ure{\~n}a- L{\'o}pez, L. Alfonso",
editor = "Balahur, Alexandra and
Mohammad, Saif M. and
Hoste, Veronique and
Klinger, Roman",
booktitle = "Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
month = oct,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6227",
doi = "10.18653/v1/W18-6227",
pages = "195--200",
abstract = "In this paper, we describe our participation in WASSA 2018 Implicit Emotion Shared Task (IEST 2018). We claim that the use of emotional external knowledge may enhance the performance and the capacity of generalization of an emotion classification system based on neural networks. Accordingly, we submitted four deep learning systems grounded in a sequence encoding layer. They mainly differ in the feature vector space and the recurrent neural network used in the sequence encoding layer. The official results show that the systems that used emotional external knowledge have a higher capacity of generalization, hence our claim holds.",
}
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<abstract>In this paper, we describe our participation in WASSA 2018 Implicit Emotion Shared Task (IEST 2018). We claim that the use of emotional external knowledge may enhance the performance and the capacity of generalization of an emotion classification system based on neural networks. Accordingly, we submitted four deep learning systems grounded in a sequence encoding layer. They mainly differ in the feature vector space and the recurrent neural network used in the sequence encoding layer. The official results show that the systems that used emotional external knowledge have a higher capacity of generalization, hence our claim holds.</abstract>
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%0 Conference Proceedings
%T SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification
%A Plaza-del-Arco, Flor Miriam
%A Martínez-Cámara, Eugenio
%A Martin, Maite
%A Ureña- López, L. Alfonso
%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 plaza-del-arco-etal-2018-sinai-iest
%X In this paper, we describe our participation in WASSA 2018 Implicit Emotion Shared Task (IEST 2018). We claim that the use of emotional external knowledge may enhance the performance and the capacity of generalization of an emotion classification system based on neural networks. Accordingly, we submitted four deep learning systems grounded in a sequence encoding layer. They mainly differ in the feature vector space and the recurrent neural network used in the sequence encoding layer. The official results show that the systems that used emotional external knowledge have a higher capacity of generalization, hence our claim holds.
%R 10.18653/v1/W18-6227
%U https://aclanthology.org/W18-6227
%U https://doi.org/10.18653/v1/W18-6227
%P 195-200
Markdown (Informal)
[SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification](https://aclanthology.org/W18-6227) (Plaza-del-Arco et al., WASSA 2018)
ACL