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- W3107636542 abstract "Sentiment analysis is the process of analyzing people's opinion and feelings toward individual, entities, issues, items or topics. Within the last couple of years, this field has gained increasing research interest varying from simple linear models to more complex neural networks models. Several challenges including the grammar, structures of the language and Morphology which one-word lead to many important meanings. The varieties of dialects and the lack of the appropriate corpora limit the use of sentiment analysis on Arabic content. Throughout this paper, we aim at providing a review on the utilization of the deep learning (DL) approach to analyze sentiments expressed in the Arabic text by using Multilayer perceptron (MLP) model. The results show that the MLP model shows highly effective performance in sentiment analysis for both Arabic and English languages." @default.
- W3107636542 created "2020-12-07" @default.
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- W3107636542 date "2020-10-01" @default.
- W3107636542 modified "2023-10-16" @default.
- W3107636542 title "Improving Sentiment Analysis in Arabic and English Languages by Using Multi-Layer Perceptron Model (MLP)" @default.
- W3107636542 cites W2903162933 @default.
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- W3107636542 doi "https://doi.org/10.1109/dsaa49011.2020.00095" @default.
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