Analysis of epidemic outbreak in Delhi using social media data

Abstract

A Social media generates a vast amount of data related to epidemic outbreak every year. Data produced by social media platform such as Twitter for health surveillance applications is exponentially increasing. Chikungunya and Dengue are taking the toll on Delhi in the year 2016 and mining twitter data reflects the status of Chikungunya and Dengue outbreak in Delhi. In this paper, the tweets extracted from twitter over a time period using epidemic - related keyword are classified using a supervised classification technique called Naïve Bayes classifier with manual tagging feature into relevant epidemic - related tweets with 90% accuracy. The relevant tweets classified are enumerated for analyzing the spread and estimating the most affected month during the outbreak and compare it with the health statistics.