Sentiment analysis becomes more popular in the research area. It assigns positive or negative polarity to an entity or items using various natural language processing methods, as well as predicts the high and poor performance of various sentiment classifiers. Our work focuses on sentiment analysis based on product reviews utilising novel text search algorithms. These reviews can be classified as positive or negative depending on specific factors in connection to a query based on phrases. We presented a hybrid strategy to identifying product reviews in this research. The results show that the proposed system approach outperforms these individual classifiers in this dataset. Cross-domain sentiment classification has drawn much attention in recent years.

Sentiment Analysis, Random Forest, Convolutional Neural Network