Tweets Sentiment Analysis for Healthcare on Big Data Processing and IoT Architecture Using Maximum Entropy Classifier

Abstract

People are too rare to discuss or talk about their health problems with each other and, it is very poor to notice about their realistic health situation. But nowadays, most of the people friendly used social media and people have started expressing their feelings and activities on it. Focus only on Twitter, users’ created tweets composed of news, politics, life conversation which can also be applied for doing a variety of analysis purposes. Therefore, healthcare system is developed to mine about the health state of Twitter user and to provide health authorities to easily check about their continental health behavior based on the Twitter data. Maximum Entropy classifier (MaxEnt) is used to perform sentiment analysis on their tweets to suggest their health condition (good, fair, or bad). It is interacting with Twitter data (big data environment) and so, Internet of Things (IoT) based big data processing framework is built to be efficiently handled large amount of Twitter user’ data. The aim of this paper is to propose healthcare system using MaxEnt classifier and Big Data processing using Hadoop framework integrated with Internet of Things architecture.