Sentiment analysis of Hinglish reviews using hybrid approaches

Abstract

People are using social media to communicate their views and opinions on several topics, and it is becoming more popular as a medium of communication. Nowadays people are curious to hear about a film review before they watch it for a few days. A summary of all reviews for a film can help users make their decision by not wasting time reading all reviews. Several websites can have summery because of the rise of social media.As a result, the words sentiment analysis and text analysis developed their paths to becoming important computational linguistics and text analysis components. Opinions are articulated in India in recent years, using multi-lingual terms. In the field of sentiment analysis, this has become a new challenge. Machine learning methods, such as neural networks, have proven effective in this task; however, there is space for advancing to networks with greater accuracy.In this investigation,U. S. English, Hindi dialects, and datasets like Twitter sentiment corpus, Amazon Product Reviews, IMDB Movie reviews, and Several public opinion datasets have been used in this study. The proposed network may achieve the greatest known accuracy of 92.25 percent. As an outcome, the success of the suggested network can be duplicated in various fields.