Date of Publication :12th April 2017

Abstract: In the recent years, social media have been emerged as major platforms for sharing information in the medical field, business, education etc. The existing system will generate a warning for adverse drugs reactions based on the negative comments from forums. The use of Latent Dirichlet Allocation modelling(LDA) in the existing system makes the data labelling process time-consuming and the polarity analysis is not done. But the proposed system uses Twitter to get the information and process on it. The information from the Twitter is extracted using Twitter API. Pre-processed tweets are stored in the database and those tweets are identified and classified whether it is based on drugs related tweets and diseases related tweets using Support Vector Machine classification(SVM). The user keywords can be predicted whether it is the best suggestion using polarity. Polarity detection is done by the keywords. Based on the number of positive tweets and the number of negative tweets it analyzes the best medicine. This system is very useful for the users to gain knowledge of the medicine

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