Multi-Layer Classification and Segmentation with Opinion Mining Learning Ensemble

Abstract

Social media has become the main area for advertising, events, campaigns, protests etc. in recent years. It offers the public a forum for expressing their opinions and beliefs to the masses. The user beliefs, habits and interests of businesses are extremely important and give users a glimpse into their thinking. Data mining is one of the tools that enables these businesses to extract useful information from user data that can be examined to generate a set of knowledge and identify a user opinion that helps companies to create user-specific products. Twitter Data Mining and other social platforms are very important since its enormous user base consists of a mixture of thoughts and opinions that may be used to anticipate results of campaigns, product assessments and similarity if correctly studied. This research provides a classification system to perform Twitter Opinion Mining Segmentation based on Ensemble Learning. The suggested approach can detect and filter out boxes and uses text segmentation for efficient text classification and voice taging.