Sentiment Analysis Classifiers for Polarity Detection in Social Media Text: A Comparative Study

People often use the internet and microblogging websites to express their thoughts and opinions on products and services. Sentiment analysis of public opinion is much more important because it aids in understanding the public's views on a specific service and the actions of the consumer who is purchasing a product. This area is expected to be extremely useful in analyzing brand awareness in both the private and public sectors. The proposed survey would aid in the comprehension of the different algorithms that are used to categorize the texts posted into various sentimental categories. The study emphasized that the hybrid algorithms outperformed supervised machine learning approaches with better classification accuracy.