Drugs categorization based on sentence polarity analyzer for Twitter data

In the recent years, social media have emerged as major platforms for sharing information in medical field, business, education etc. Social media provides limitless opportunities for patients to share experiences with their drug usage. In current scenarios and with available new technologies, Twitter can be used effectively for gathering information rather than gathering information in traditional method. Twitter is the most popular online social networking service that enable user to share and gain knowledge. Doctors says that the medical information shared by doctors and patients on their social media is valuable and trustable. Twitter is used as a prominent Social Media to share their experience based on drugs and diseases. The Drugs Categorization based on Sentence Polarity Analyzer (DCSPA) collects the drugs and disease related tweets from Twitter. Tweet collection is done using Twitter API. The collected tweets are preprocessed and then classifying the tweets related to drugs and diseases is done using Support Vector Classification (SVM). After classification, the tweets are analyzed based on polarity of the sentence. The sentence polarity analyzer is used to categorize the drugs or disease as positive, negative or neutral feedback. The experimental results shows that the sentence polarity analyzer provides better categorization of tweets based on its polarity.