Sentiment Analysis as Prediction Tool in Multiple Domain Applications

Abstract

Sentiment Analysis is considered as a tool for prediction. The use of sentiment analysis is in multiple domain applications. The list of domain specific areas is exhausted where sentiment analysis is applied. Some of the real life domain specific areas of sentiment analysis are as services sector, healthcare, sports, fashion, politics, business sector, financial services, movies reviews, stock market reviews, book reviews, and social relations. The sentiments analysis and opining mining is made by various researchers from time to time. The techniques suggested by various authors are mainly classification, clustering, machine learning, natural language processing techniques, supervised pattern discovery method, quantification, fuzzy neural network, correlation, probabilistic model, regression, probabilistic model, supervised learning. Although various techniques are presented by various authors still there is vast scope of research for deploying best sentiment analysis mechanisms specifically on the basis of its explicit domain of applications.