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Investigating Deep Learning Word2vec Model for Sentiment Analysis in Arabic and English languages for User’s reviews

机译:研究用于阿拉伯语和英语的情感分析的深度学习Word2vec模型以供用户评论

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In this paper, we explore natural language processing (NLP) methods to perform sentiment analysis or opinion mining. In addition, we show an application on English and Arabic sentiment analysis by implementing sentiment classification for three datasets which are Booking hotel dataset, Food fine Amazon dataset and Arabic movie review dataset. We applied Word2Vec model followed by Random Forest classifier (RF) for Arabic movie dataset. The results show that the Word2Vec model shows highly effective performance in sentiment analysis for English language datasets but it does not work for Arabic language as Arabic language need different mechanism.
机译:在本文中,我们探索了自然语言处理(NLP)方法来执行情感分析或观点挖掘。此外,我们通过对三个数据集(预订酒店数据集,美食亚马逊数据集和阿拉伯电影评论数据集)执行情感分类来展示英语和阿拉伯语情感分析的应用程序。我们对阿拉伯电影数据集应用了Word2Vec模型,然后应用了随机森林分类器(RF)。结果表明,Word2Vec模型在英语语言数据集的情感分析中显示出非常有效的性能,但不适用于阿拉伯语,因为阿拉伯语需要不同的机制。

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