Sentiment classification of social media reviews using an ensemble classifier

Savita Sangam, Subhash Shinde


These days it has become a common practice for business organizations and individuals to make use of social media for sharing the opinions about the products or the services.  Consumers are also ready to share their views on certain products or commodities.  Thus huge amount of unstructured social media data gets generated day by day. Gradually heap of text data will be formed in many areas like automated business, education, health care, and show business and so on. Opinion mining also referred as sentiment analysis or sentiment classification, deals with mining of the review text and classifying the opinions or the sentiments of that text as positive or negative. In this paper we propose an ensemble classifier model consisting of Support Vector Machine and Artificial Neural Network. It combines the knowledge from two feature sets for sentiment classification. The proposed model shows the acceptable performance in terms of accuracy when compared with the baseline model.


ANN, Ensemble model, Feature selection, Opinion mining, Reviews, Sentiment classification, SVM.

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