@inproceedings{ghoul-lejeune-2021-sarcasm,
title = "Sarcasm and Sentiment Detection in {A}rabic: investigating the interest of character-level features",
author = {Ghoul, Dhaou and
Lejeune, Ga{\"e}l},
booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
month = apr,
year = "2021",
address = "Kyiv, Ukraine (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wanlp-1.41",
pages = "329--333",
abstract = "We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.",
}
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<abstract>We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.</abstract>
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%0 Conference Proceedings
%T Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features
%A Ghoul, Dhaou
%A Lejeune, Gaël
%S Proceedings of the Sixth Arabic Natural Language Processing Workshop
%D 2021
%8 apr
%I Association for Computational Linguistics
%C Kyiv, Ukraine (Virtual)
%F ghoul-lejeune-2021-sarcasm
%X We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.
%U https://aclanthology.org/2021.wanlp-1.41
%P 329-333
Markdown (Informal)
[Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features](https://aclanthology.org/2021.wanlp-1.41) (Ghoul & Lejeune, WANLP 2021)
ACL