Text Mining from Social Media for Public Health Applications

Public Health is crucial to manage and monitor threats to the health of the population. In recent years, Twitter has been successfully applied to monitor diseases through its ability to provide near real-time data and proved to be an asset to the domain. This research aims to further explore capabilities of Twitter in the disease surveillance field by focusing on its geolocation feature and health mentions, identifiable through disease-specific language patterns present in Twitter messages.