An Artificial intelligence Approach to Fake News Detection in the Context of the Morocco Earthquake
DOI:
https://doi.org/10.56294/dm2024.377Keywords:
Fake news, information, Social media, Information ver- ification, Deep learning models, Natural language processing, machine learningAbstract
The catastrophic earthquake that struck Morocco on Septem- ber 8, 2023, garnered significant media coverage, leading to the swift dissemination of information across various social media and online plat- forms. However, the heightened visibility also gave rise to a surge in fake news, presenting formidable challenges to the efficient distribution of ac- curate information crucial for effective crisis management. This paper introduces an innovative approach to detection by integrating Natural language processing, bidirectional long-term memory (Bi-LSTM), con- volutional neural network (CNN), and hierarchical attention network (HAN) models within the context of this seismic event. Leveraging ad- vanced machine learning,deep learning, and data analysis techniques, we have devised a sophisticated fake news detection model capable of precisely identifying and categorizing misleading information. The amal- gamation of these models enhances the accuracy and efficiency of our system, addressing the pressing need for reliable information amidst the chaos of a crisis.
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Copyright (c) 2024 Imane Ennejjai, Anass Ariss , Yasser Fouad, Abdulatif Alabdultif, Rajasekhar Chaganti, Karima Salah Eddine, Asmaa Lamjid, Soumia Ziti (Author)
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