A Review on Sentiment Analysis and Opinion Mining

Sentiment analysis (SA) is the process of computationally recognizing and classifying the opinions conveyed within a piece of text or some other forms of information. This paper underscores the significance of sentiment analysis (SA) that serves as a vital tool for businesses, aiding in customer understanding and facilitating informed decision-making. The study includes a review of the literature on many machine learning methods in addition to deep learning models. Furthermore, the paper delves into the utilization of nature-inspired algorithms for feature selection in the context of sentiment analysis (SA), and examples include Particle Swarm Optimization, Firefly Algorithms and Genetic Algorithms among others. These nature-inspired algorithms are chosen to iteratively search for optimal feature subsets, aiding in enhancing the overall efficacy of sentiment analysis methodologies.