Open AccessPREDICTING RATINGS FOR USER REVIEWS AND OPINION MINING ANALYZE FOR PHYSICIANS AND HOSPITALS
Author(s) -
Hema Sagar Vakati,
R. Jebakumar
Publication year - 2017
Publication title -
asian journal of pharmaceutical and clinical research
Language(s) - English
Resource type - Journals
eISSN - 2455-3891
pISSN - 0974-2441
DOI - 10.22159/ajpcr.2017.v10i3.16094
Subject(s) - helpfulness , sentiment analysis , the internet , health care , computer science , opinion leadership , psychology , internet privacy , medicine , world wide web , public relations , artificial intelligence , political science , social psychology , law
Health care is taking its turn in the internet now and online health information consumption is also booming. Users have started generating healthcarereports like online doctor reviews open to all. Hence, online health forums are increasingly popular these days since people can gather their requireddata by just sitting at home and select the best doctor by considering the reviews available online. The patients also browse on their concerneddiseases and use the open forum for discussion on the topics. On an average, these online health-care providers are mainly focusing on reviews aboutthe physicians. The feedback provided by patients is considered and we also analyze the sentiments of the patient to estimate the value of the reviews.The rating for the doctors is divided into various categories such as Staff, Knowledge, and Helpfulness. We propose support vector machine and apriorifor the classification of data and use sentiment based rating prediction to analyze doctor’s reviews and opinion mining patterns for online patterns.By providing physician ratings in website, it offers the patients to know about the physician and consider the critique and information to make theirdecision.Keywords: Support vector machine, Apriori, Sentiment classification, Opinion mining.