M.V.Anish Kumar, K.Mahalakshmi, P.Sherubha and K. Narmatha
Sentiment Analysis is the process for determining the semantic orientation of the reviews. There are many algorithms existing for the sentiment classification. Support Vector Machines (SVM) are a specific type of machine learning algorithm used for many statistical learning problems, such as text classification, face and object recognition, handwriting analysis, spam filtering and many others. We have studied the SVM as the recent machine learning method for sentiment classification, this method later suppressed by using feature extraction method. In this paper we are extending SVM and investigating the method by adding the parallel processing methods of sentiment classification such as MapReduce and Hadoop. The combinational evaluation method of SVM with and without MapReduce is presented in this work.
Sentiment Analysis, Support Vector Machine (SVM), Text Mining, Feature Extraction, MapReduce, Hadoop.