Date of Publication :23rd March 2018

Abstract: The study of sentimental analysis and opinion mining deals with attitude and emotions. Opinion mining has several challenges. The first challenge is that a word is either positive in one situation or negative in another situation. Therefore, sentiment can be performed using social media messages.. To overcome this problem, social media messages are used which are free of cost and produced in world wide. In this the public concern can be measured using two-step word alignment approach. In the first step, raw reviews are separated into personal reviews and news reviews. In the second step, personal reviews are further classified into personal negative and personal non-negative. In both steps, the trained data is generated automatically using an emotional-oriented, clue-based method and the trained dataset can be tested using machine learning model such as Naïve Bayes. The proposed algorithm will increase the accuracy for epidemic domain

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