WANLP 2021 Shared-Task: Towards Irony and Sentiment Detection in Arabic Tweets using Multi-headed-LSTM-CNN-GRU and MaRBERT

Reem Abdel-Salam


Abstract
Irony and Sentiment detection is important to understand people’s behavior and thoughts. Thus it has become a popular task in natural language processing (NLP). This paper presents results and main findings in WANLP 2021 shared tasks one and two. The task was based on the ArSarcasm-v2 dataset (Abu Farha et al., 2021). In this paper, we describe our system Multi-headed-LSTM-CNN-GRU and also MARBERT (Abdul-Mageed et al., 2021) submitted for the shared task, ranked 10 out of 27 in shared task one achieving 0.5662 F1-Sarcasm and ranked 3 out of 22 in shared task two achieving 0.7321 F1-PN under CodaLab username “rematchka”. We experimented with various models and the two best performing models are a Multi-headed CNN-LSTM-GRU in which we used prepossessed text and emoji presented from tweets and MARBERT.
Anthology ID:
2021.wanlp-1.37
Volume:
Proceedings of the Sixth Arabic Natural Language Processing Workshop
Month:
April
Year:
2021
Address:
Kyiv, Ukraine (Virtual)
Editors:
Nizar Habash, Houda Bouamor, Hazem Hajj, Walid Magdy, Wajdi Zaghouani, Fethi Bougares, Nadi Tomeh, Ibrahim Abu Farha, Samia Touileb
Venue:
WANLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
306–311
Language:
URL:
https://aclanthology.org/2021.wanlp-1.37
DOI:
Bibkey:
Cite (ACL):
Reem Abdel-Salam. 2021. WANLP 2021 Shared-Task: Towards Irony and Sentiment Detection in Arabic Tweets using Multi-headed-LSTM-CNN-GRU and MaRBERT. In Proceedings of the Sixth Arabic Natural Language Processing Workshop, pages 306–311, Kyiv, Ukraine (Virtual). Association for Computational Linguistics.
Cite (Informal):
WANLP 2021 Shared-Task: Towards Irony and Sentiment Detection in Arabic Tweets using Multi-headed-LSTM-CNN-GRU and MaRBERT (Abdel-Salam, WANLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.wanlp-1.37.pdf
Data
ArSarcasm-v2