Sentiment Mining Approaches for Big Data Classification and Clustering

Abstract

Sentiment analysis is one of the most important applications in the field of text mining. It computes people's opinions, comments, posts, reviews, evaluations, and emotions which are expressed on products, sales, services, individuals, organizations, etc. Nowadays, large amounts of structured and unstructured data are being produced on the web. The categorizing and grouping of these data become a real-world problem. In this chapter, the authors address the current research in this field, issues and the problem of sentiment analysis on Big Data for classification and clustering. It suggests new methods, applications, algorithm extensions of classification and clustering and software tools in the field of sentiment analysis.