Summarization and Sentiment Analysis from User Health Posts

Abstract

Health communities offer huge variety of Information regarding Medical sector which is useful for Drug dealers, Doctors and patients. This work includes the collection of Real time health posts from trusted websites, these websites contain patients experiences and side effects on drugs used by them. By collecting these information from trusted websites, this paper perform summarization of user posts per drug and come out with useful conclusions for Drug dealers, Doctors, Patients.

Further, It classify the users based on their ‘emotional state of mind' In this paper it perform the knowledge discovery from user post, which gives useful ‘Patterns', ‘Keyword extraction', by using Association rule Method.