Abstract
Sarcasm detection and sentiment analysis are important tasks in Natural Language Understanding. Sarcasm is a type of expression where the sentiment polarity is flipped by an interfering factor. In this study, we exploited this relationship to enhance both tasks by proposing a multi-task learning approach using a combination of static and contextualised embeddings. Our proposed system achieved the best result in the sarcasm detection subtask (Abu Farha et al., 2021).
Original language | English |
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Title of host publication | Proceedings of the Sixth Arabic Natural Language Processing Workshop |
Editors | Nizar Habash, Houda Bouamor, Hazem Hajj, Walid Magdy, Wajdi Zaghouani, Fethi Bougares, Nadi Tomeh, Ibrahim Abu Farha, Samia Touileb |
Publisher | Association for Computational Linguistics, ACL |
Pages | 318-322 |
Number of pages | 5 |
ISBN (Electronic) | 9781954085091 |
Publication status | Published - 30 Apr 2021 |
Event | 6th Arabic Natural Language Processing Workshop, WANLP 2021 - Virtual, Kyiv, Ukraine Duration: 19 Apr 2021 → 19 Apr 2021 |
Publication series
Name | Workshop on Arabic Natural Language Processing (WANLP) |
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Conference
Conference | 6th Arabic Natural Language Processing Workshop, WANLP 2021 |
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Country/Territory | Ukraine |
City | Kyiv |
Period | 19/04/21 → 19/04/21 |
Bibliographical note
Publisher Copyright:© WANLP 2021 - 6th Arabic Natural Language Processing Workshop
ASJC Scopus subject areas
- Language and Linguistics
- Computational Theory and Mathematics
- Software
- Linguistics and Language