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To address this gap, unstructured Arabic texts have been studied in this work owing to their abundant appearance in social media Web sites. This work addresses the difficulty of handling unstructured social media texts, particularly when the data at hand is very limited. This intelligent data augmentation technique that handles the problem of less availability of data are used. This article has proposed a novel architecture for hand Arabic words classification and understands based on convolutional neural networks (CNNs) and recurrent neural networks. Moreover, the CNN technique is the most powerful for the analysis of Arabic tweets and social network analysis. The main technique used in this work is character-level CNN and a recurrent neural network stacked on top of one another as the classification architecture. 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