Twitter sentiment analysis in healthcare using Hadoop and R

Healthcare is a data-rich industry. Big data is fast, expanding rapidly and is highly varied. Twitter can serve as an important data source for providing real-time information that has stimulated companies in diverse domains to understand their consumers. In the healthcare field we will concentrate on patients, the illness they were suffering from, the hospital they preferred at the time of sickness, service provided to them and were they satisfied or not. The era of social media generates an enormous amount of data for analysis. The outcome information is beneficial for the health of individuals. Analyzed information is further used for the recommendation of hospitals at the time of ailment. Health care is still a nascent field undergoing rapid change and evolution due to continuous enhancements in medicine. It is based on the opinion and satisfaction rate of the patients. This work is conducted through an online survey and then based on the satisfaction rate, the hospitals are selected. The messages posted in Twitter called tweets are used for comparison of the sentiments of the patients that are correlated to the hospitals selected. The comparison shows the popularity of a hospital among patients at the time of ailment.