An Analysis on Data Mining for Sentiment Analysis Using Different Classification Algorithms

A rapid rise in the field of data mining has occurred in recent years. Analysis of Sentiment is an idea that includes numerous happenings including sentiment extraction, classification of sentiment, classification of subjectivity, a summary of the opinion, or spam detection amongst others. opinion mining (OM) or Sentiment analysis (SA) is a mathematical study of views, emotions, sentiments, assessments, and behaviors of people, including products, organizations, services, issues, individuals, topics, events also their attributes. The advancement in web technology tools has given rights to their users to share their opinions on things that they interact with within their daily life. They can post it online on different platforms available. This massive amount of data is used to find out major curiousness that concerns people most and is very beneficial to many firms. To get benefited from this unstructured, inconsistent data written in natural language, first, it needs to be clean and transform and then we will be able to perform different operations like classification and aspect-based sentiment analysis. In this paper, we have thoroughly discussed 4 data mining algorithms utilized for prediction & classification.