A Review on Sentiment Analysis using Machine Learning

Sentiment Analysis [SA] is a method that is used to detect the state of some information or text. It can be applied to tasks such as text classification and summarization, and various methods can be used to extract sentiment from text, including machine learning algorithms and rule-based systems. Sentiment analysis is an important tool for businesses to understand customer feedback and measure customer satisfaction and loyalty. It classifies the given text into three categories: positive, negative, or neutral. The statement “the picture quality of TV is good” expresses a positive opinion about a particular TV, while “the sound is not adequate” expresses a negative opinion. Recent challenges with sentiment analysis indude capturing sarcasm, emotion in text and dealing with long texts. The paper presents a literature survey of many machine learning techniques as well as deep learning models such as CNN, LS TM, etc.