Sarcasm Detection in Arabic Tweets: A comparison Between deep learning and Pre trained Transformers-based Models

Abstract

Sarcasm is one of the main challenges of sentiment analysis systems. This paper mainly focuses on the recognition of Arabic sarcasm on Twitter. Recognizing sarcasm in tweets is essential for understanding users' opinions on various topics and events. There are only a few attempts regarding saracsm detection in Arabic due to the challenges and complexity of the Arabic language. We propose in this paper a comparison between traditional neural network-based models and pre-trained transformers. The experimental results show that transformers are a promising approach for the task of Arabic sarcasm detection.