Ensemble based Hybrid Machine Learning Approach for Sentiment Classification- A Review

Abstract

Due to digital explosion, huge amount of data is generated from different sources which require critical analysis for decision making. In recent days one of the challenging issues like sentiment classification has drawn the attention of many researchers working in the area of opinion mining. The supervised machine learning technique is used for analyzing sentiments associated with unstructured text data. But, recently it has been observed from the findings that ensemble based learning algorithm achieves better understanding and acceptance of the solution in terms of diversity and accuracy. In this paper, an extensive study of ensemble based machine learning techniques in the domain of sentiment classification has been done to enhance the efficiency, by adopting multiple learning algorithms to obtain better predictive performance, that would be obtained from any of the constituent learning algorithms. Again, how the analysis will become stronger, some suggestions are proposed at the end of the discussion.