Research Article
Opinion Mining for the Tweets in Healthcare Sector using Fuzzy Association Rule
@ARTICLE{10.4108/eai.13-7-2018.159861, author={Mamta Mittal and Iqbaldeep Kaur and Subhash Chandra Pandey and Amit Verma and Lalit Mohan Goyal}, title={Opinion Mining for the Tweets in Healthcare Sector using Fuzzy Association Rule}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={4}, number={16}, publisher={EAI}, journal_a={PHAT}, year={2018}, month={10}, keywords={Health, Social Media Analysis, Twitter Mining, Sentimental Analysis, Text Mining, Association Rule}, doi={10.4108/eai.13-7-2018.159861} }- Mamta Mittal
Iqbaldeep Kaur
Subhash Chandra Pandey
Amit Verma
Lalit Mohan Goyal
Year: 2018
Opinion Mining for the Tweets in Healthcare Sector using Fuzzy Association Rule
PHAT
EAI
DOI: 10.4108/eai.13-7-2018.159861
Abstract
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 by making 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 in this 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.
Copyright © 2018 Mamta Mittal et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
