: Fake news has spread more widely over the past few years. The development of social media andinternet websites has fueled the spread of fake news, causing it to mix with accurate information. The majority ofstudies on Fake News Detection FND were in English, but recent attention has been focused on Arabic. However,there aren't many studies on Arabic fake news detection. In this work, a new Arabic fake news detection approachhas been proposed using Arabic dataset publically available and a translated English fake news dataset into Arabic.A new model Text-CNNs based on 1D Convolution Neural Networks CNNs has been used for classification realand fake news. Extensive experimental results on the Arabic fake news dataset show that our proposed approachprovided high detection accuracy about (99.67%), Precision (99.45), Recall (99.65) and F1-score (99.50).
No takes yet. Share an insight, caveat, or question.
Alhity et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: