A survey on prediction approaches for epidemic disease outbreaks based on social media data

Abstract

Currently, in order to recognize the Epidemic diseases in the earlier stage, social media and search queries are the most reliable source of data to mine and obtain new information about current activities. These interactive groups play a significant role where users give data of their likings and acquaintances. This data can be utilized to quantify the impact of thoughts and the general public conclusions continuously, being helpful on a few fields and research regions, for example, advertising efforts, budgetary expectation or open Medicare applications among others. Recently there are many techniques and approaches were handled by the researchers for monitoring the web data sources in order to identify the health measures of the public has developed as another important imperative so-called Epidemic Intellect. For early discovery of disease outbreaks in order to decrease the effect of epidemics by monitoring, several intelligence systems were generally used by the health care organizations. In this paper, the literature review is based on the different prediction methods and their approaches to extract web data from social medias like Facebook and twitter which are all gained much attention on early disease detection for public wellbeing. Among 60 papers related to prediction of epidemic outbreaks using social media data are reviewed and analyzed based on various diseases and prediction approaches.