Opinion Mining for the Tweets in Healthcare Sector using Fuzzy Association Rule - Mamta Mittal; Iqbaldeep Kaur; Subhash Pandey; Amit Verma; Lalit Goyal (EAI Endorsed Transactions on Pervasive Health and Technology, 2018)
Communication among several internet users has become more convenient through social networking sites to where each user sharing his own opinions on different matters, such as Healthcare, Education, marketing etc. The Objective of this paper is to present a method to make it easier for even a layman to predict and analyze one’s health issues on his own bymaking use of tweets on the social website twitter.com. As far as methodology or techniques is concerned, an algorithm has been framed for the same to perform the analysis on health care tweets with association rules to classify the ailments and their symptoms using a corpus through fuzzy set and two step approach for Document Term Matrix & Term Document Matrix. The results demonstrate the comparison of different terms over the WordCloud which concludes that inthis novel approach of two step authentication the average accuracy of association between the hiv ailments is 98% through correlation table and association between the HIV ailments with 98% correlation.