Sentiment Analysis Using Machine Learning Techniques: Systematic Study

Abstract

People have always had an interest in what people think, or what their sentiments and opinion is. Since the inception of the internet, increasing numbers of people are using websites and services to express their opinion and sentiments in the form of tweets. With social media channels such as Facebook, LinkedIn, and Twitter, it is becoming feasible to automate and gauge what public opinion is on a given topic, news story, product, or brand. Sentiments that are mined from such services can be valuable. Datasets that are gathered can be analyzed and presented in such a way that it becomes easy to identify if the online mood is positive, negative, and neutral. In this paper, it is summarized about the essential need for sentiment analysis and its challenges. This also explains the sentiment analysis and the process and challenges involved in the sentiment analysis.