Research Area:  Machine Learning

Abstract:

This paper presents the ArabicProcessors teams system designed for sarcasm (subtask 1) and sentiment (subtask 2) detection shared task. We created a hybrid system by combining rule-based features and both static and dynamic embeddings using transformers and deep learning. The system-s architecture is an ensemble of Naive bayes, MarBERT and Mazajak embedding. This process scored an F1-score of 51 percent on sarcasm and 71 percent for sentiment detection.

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Author(s) Name:  Kamel Gaanoun, Imade Benelallam

Publisher name:  ACN

DOI:  

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Paper Link:   https://aclanthology.org/2021.wanlp-1.45/