Tracking Coronavirus Pandemic Diseases using Social Media: A Machine Learning Approach

With the increasing use of social media, a growing need exists for systems that can extract useful information from huge amounts of data. While, People post personal data interactively, an outbreak of an epidemic event can be noticed from these data. The issue of detecting the route of pandemic diseases is addressed. The main objective of this research work is to use a dual machine learning approach to evaluate current and future data of Covid-19 cases based on published social media information in specific geographical region and show how the disease spreads geographically over the time. The dual machine learning approach used based on traditional data mining methods to estimate disease cases found in social media related to specific geographical region. On other hand, sentiment analysis is conducted to assess the public perception of the disease awareness on the same region.