Topic Model Based Opinion Mining and Sentiment Analysis

Abstract

This paper discusses a new topic model based approach for opinion mining and sentiment analysis of text reviews posted in web forums or social media site which are mostly in unstructured in nature. In recent years, opinions are exchanged in clouds about any product, person, event or any interested topic. These opinions help in decision making for choosing a product or getting feedback about any topic. Opinion mining and sentiment analysis are related in a sense that opining mining deals with analyzing and summarizing expressed opinions whereas sentiment analysis classifies opinionated text into positive and negative. Aspect extraction is a crucial problem in sentiment analysis. Model proposed in the paper utilizes topic model for aspect extraction and support vector machine learning technique for sentiment classification of textual reviews. The goal is to automate the process of mining attitudes, opinions and hidden emotions from text.