查看文章

Sentiment analysis aims to classify a text according to sentimental polarities of people’s opinions, such as positive, negative, or neutral. While most of the studies focus on eliciting features from English text, the research on Arabic is limited due to the morphological and grammatical complexity of Arabic language. In this paper, we proposed an optimized sentiment classification for dialectal Arabic short text at the document level using deep learning (DL). The contributions of this paper are in three areas. First, we extracted semantic features for Arabic short text at the word level and character level. Second, we used three DL topologies for classification models: a long short-term memory recurrent neural network (LSTM); a convolutional neural network (CNN); and an ensemble model combining both models’ advantages to improve the prediction performance. Third, we used a hyperparameter tuning estimation method …