Revue de l'Information Scientifique et Technique
Volume 27, Numéro 2, Pages 62-65
2023-11-08
Modeling Fake News Detection Using Machine Learning Algorithms For Arabic Covid-19 Tweets
Authors : Aldawsari Mohammed . Salih Dawood Omer Omer . Yousra F.g Elhakeem . Safa Eltayeb .
Abstract
Fake news has become a major issue in the digital age, with social media playing a major role in its spread. This paper outlines the dataset and methodology used to model Arabic fake news. The dataset used is the shared Arabic fake news dataset in twitter. The model used for this task is a simple transformer fake news model based on the arabic pre-trained language model CAMeL-BERT. This model was utilized in two variants: a fine-tuned model and a Bidirectional long short-term model . The experiment results of this modeling CAMeL-BERT provides the best result by achieving 0.959 F1, thus outperforming all other models variants in detecting fake news.
Keywords
Fake news detection ; machine learning ; covid-19 twitter ; CAMeL-BERT
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