Revue d'Information Scientifique et Technique

Classifying Arabic covid-19 related tweets for fake news detection and sentiment analysis with BERT-based models

The present paper is about the participation of our team “techno” at CERIST Natural Language Processing Challenge. We used an available dataset for task1.c: Arabic sentiment analysis and fake news detection within covid-19. It comprises 4128 tweets for sentiment analysis task and 8661 tweets for fake news detection task. We used natural language processing tools with the combination of the most renowned pre-trained language models BERT (Bidirectional Encoder Representations from Transformers). The results shows the efficacy of pre-trained language models as we attained an accuracy of 0.93 for the sentiment analysis task and 0.90 for the fake news detection task.

Auteurs : Rabia Bounaama , Mohammed El Amine Abderrahim

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