Improving Sentence Polarity Determination In Sentiment Analysis based on RNN and LSTM Deep Learning Algorithm

Today, due to the large volume of opinions published by people in cyberspace, sentiment analysis plays a key role in extracting information. One of the new techniques based on studies has been done to determine the exact polarity of the sentence in sentiment analysis is deep learning algorithms. In this research, two deep learning algorithms, namely RNN and LSTM, has been used to determine sentence polarity in order to achieve more accurate results. Moreover, in the proposed technique, pre-trained word embedding algorithm, namely Wordtovec, was used to determine the semantic relationships between words to increase the accuracy of the proposed method. The proposed method was evaluated on two data sets; airline-tweet and IMDB. The evaluation results show that on the airline-tweet dataset, the proposed method has an accuracy of 0.78 and accuracy of 0.84 on the IMDB data set.