Opinion Mining For Text Data: An Overview

Abstract

Abstract: Nowadays there is huge growth in data People post their views and opinions through the web on different apps, blogs, articles, etc. Customers post their reviews on shopping sites about the product or service. So, it becomes beneficial for companies, manufactures, business owners and sellers to understand customers, product users or buyers but due to huge data/feedbacks or posted opinions manually analyzing text data, is impossible to do. So, opinion mining is very important so as to analyze all the data and know the sentiments from that data without much human effort and in less time huge data can be analyzed. Many researches have made the base in this field of opinion mining. Here opinion mining will be discussed starting with what is opinion mining, how opinion mining is performed, levels, types and approaches for opinion mining, and applications. Also, methods for Text Preprocessing, Feature Extraction, Evaluation and Classification Approaches that are Machine Learning approaches and Lexicon Based approaches also, various opinion mining methods such as Support Vector machines (SVM), Neural Network, Naïve Bayes, Bayesian Network, Maximum Entropy, Corpus and Dictionary based methods are discussed here.